ROMANIAJUDETUL PRAHOVA

_ PRIMARIA ORASULUI BREAZA__

ORAS BREAZA, Str.Republicii, nr.82B;Cod fiscal:2845486;Telefon: 0244 340 508; 0244 341 460; Fax: 0244 340 428

e-mail:primariabreaza@yahoo.comweb site:www.primariabreaza.ro

Incepand cu anul 2008, Primaria orasului Breaza a derulat Proiectul „Retirement-a sense of purpose trogh an intercultural dialogue”, in cadrul Programului national- „Invatare pe tot parcursul vietii”, in parteneriat cu patru state europene, respectiv Cipru, Italia si Lituania si Tara Galilor.

Obiectivul principal al acestui proiect este promovarea dialogului intercultural, ce cuprinde actiuni de promovare si transmitere a traditiilor de la o generatie la alta.

Fiecare stat partener , pe parcursul derularii proiectului va realiza o carte cu CD in limba engleza si in limba materna a celor 4 state partenere,pe diverse teme, cum ar fi:mestesuguri traditionale, arta culinara,mituri locale si cantece traditionale.

In vederea identificarii nevoilor persoanelor varstnice, in cadrul proiectului a fost aplicat chestionarul, al carui rezultat il redam mai jos.

CrosstabsCase Processing Summary

266 100.0% 0 .0% 266 100.0%266 100.0% 0 .0% 266 100.0%266 100.0% 0 .0% 266 100.0%266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

266 100.0% 0 .0% 266 100.0%

Gender * CountryGender * AgeGender * NationalityGender * StudiesGender * LivingconditionsGender * With whom doyou live?Gender * Are you inemployment?Gender * Did you workbefore your retirement?Gender * Every day Iattend a place of worshipand then go homeGender * Every day I stayat homeGender * Every day I visitmy children/ relatives/friendsGender * Every day I visit /Restaurants /entertainmentGender * I am givenassistance and supportbyGender * I need help withshoppingGender * I need help withcleaningGender * I need help withcleaning my houseGender * I need help withpersonal care (bathroom,toilet,...)Gender * I need help withnursing careGender * I need help toarrange my personalaffairs (bank, servises)Gender * I need help withtransport to doctor or tohospitalGender * I need help withlonliness (I needcompany)Gender * I need help totake care about my petGender * I feel lonelyGender * I am satisfiedwith my lifeGender * I feel that myfamily cares about meGender * Is there aVoluntary Organisation forsupport for Elder peoplein your city?Gender * Are youinterested in developingof the idea to establish aCentre for Elder people?Gender * Are thereenough opportunities forentertainment andparticipating in activities inyour area?Gender * A centre forolder people I would liketo offer to me a betterhealth careGender * A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterestsGender * A centre forolder people I would liketo offer to me visits/tripsGender * A centre forolder people I would liketo offer to meentertainmentopportunitiesGender * A centre forolder people I would liketo offer to meopportunities forincreasing activitiesGender * A centre forolder people I would liketo offer to me foodGender * Elderly peopledon't need lectures,theatrical plays and trips,they only need caring andfood.Gender * Young peopleneed good companymore than elderly people.Gender * People, in spiteof their age, want to learnand be active.Gender * Elderly peoplecan enjoy life as youngerpeople do.Gender * I would likecomputer lessonsGender * I would likecooking lessonsGender * I would likedancing lessonsGender * I would like artand crafts lessonsGender * I would likepottery lessonsGender * I would likeforeing languageslessonsGender * I would like mycountries' language forforeignersGender * I would likegymnastics lessonsGender * I would likefashion-embroiderylessonsGender * I would likediscussion on a variety oftopicsGender * To participate ina team to publish a bookwith traditional recipesGender * To participate ina team to publish a bookwith traditional myths andstoriesGender * To participate ina team to publish a bookwith old pictures from ourcity or townGender * To participate ina team to publish a touristguide about our city ortownGender * To participate ina team to publish a bookwith traditional songs

N Percent N Percent N PercentValid Missing Total

Cases

Gender * CountryCrosstab

Count

29 27 19 8 8371 69 24 19 183

100 96 43 27 266

MaleFemale

Gender

Total

Cyprus Lithuania Romania WalesCountry

Total

Chi-Square Tests

4.057a 3 .2553.874 3 .275

.890 1 .346

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 8.42.

a.

Symmetric Measures

.124 .255

.124 .255266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

60

40

20

0

Country

Cyprus

Lithuania

Romania

Wales

Gender * AgeCrosstab

Count

13 31 31 8 8360 55 40 28 18373 86 71 36 266

MaleFemale

Gender

Total

50-59 60-69 70-79 80+Age

Total

Chi-Square Tests

13.528a 3 .00413.968 3 .003

2.545 1 .111

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 11.23.

a.

Symmetric Measures

.226 .004

.226 .004266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

Age

50-59

60-69

70-79

80+

Gender * NationalityCrosstab

Count

78 5 83171 12 183249 17 266

MaleFemale

Gender

Total

Local OtherNationality

Total

Chi-Square Tests

.027b 1 .869

.000 1 1.000

.027 1 .8681.000 .554

.027 1 .869

266

Pearson Chi-SquareContinuity Correctiona

Likelihood RatioFisher's Exact TestLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

Exact Sig.(1-sided)

Computed only for a 2x2 tablea.

0 cells (.0%) have expected count less than 5. The minimum expected count is5.30.

b.

Symmetric Measures

.010 .869

.010 .869266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

200

100

0

Nationality

Local

Other

Gender * StudiesCrosstab

Count

0 13 23 22 15 10 832 38 50 42 32 19 1832 51 73 64 47 29 266

MaleFemale

Gender

Total

Missing

I only studiedfew classes in

PrimarySchool

I graduatedfrom Primary

School

I graduatedfrom

SecondarySchool

I graduatedfrom Lyceum

(Higherschool) (FE)

I graduatedfrom

college/university (HE)

Studies

Total

Chi-Square Tests

2.142a 5 .8292.753 5 .738

1.197 1 .274

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

2 cells (16.7%) have expected count less than 5. Theminimum expected count is .62.

a.

Symmetric Measures

.090 .829

.090 .829266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

60

50

40

30

20

10

0

Studies

Missing

I only studied few c

lasses in Primary Sc

I graduated from Pri

mary School

I graduated from Sec

ondary School

I graduated from Lyc

eum (Higher school)

I graduated from col

lege/university (HE)

Gender * Living conditionsCrosstab

Count

1 21 61 0 833 71 108 1 1834 92 169 1 266

MaleFemale

Gender

Total

Missing Yes No 3.00Living conditions

Total

Chi-Square Tests

5.416a 3 .1445.844 3 .119

2.865 1 .091

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. Theminimum expected count is .31.

a.

Symmetric Measures

.143 .144

.143 .144266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

Living conditions

Missing

Yes

No

3.00

Gender * With whom do you live?Crosstab

Count

19 42 5 15 2 8356 63 30 27 7 18375 105 35 42 9 266

MaleFemale

Gender

Total

Missing

With myhusband/wife/partner

With mychildren

With myhusband/wife/partner andmy children

With otherpeople

With whom do you live?

Total

Chi-Square Tests

10.391a 4 .03411.003 4 .027

.371 1 .542

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

1 cells (10.0%) have expected count less than 5. Theminimum expected count is 2.81.

a.

Symmetric Measures

.198 .034

.198 .034266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

With whom do you liv

Missing

With my husband/w ife

/partner

With my children

With my husband/w ife

/partner and my chil

With other people

Gender * Are you in employment?Crosstab

Count

0 16 67 834 40 139 1834 56 206 266

MaleFemale

Gender

Total

Missing Yes NoAre you in employment?

Total

Chi-Square Tests

2.162a 2 .3393.342 2 .188

1.931 1 .165

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

2 cells (33.3%) have expected count less than 5. Theminimum expected count is 1.25.

a.

Symmetric Measures

.090 .339

.090 .339266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

160

140

120

100

80

60

40

20

0

Are you in employmen

Missing

Yes

No

Gender * Did you work before your retirement?Crosstab

Count

13 61 9 8332 112 39 18345 173 48 266

MaleFemale

Gender

Total

Missing Yes No

Did you work before yourretirement?

Total

Chi-Square Tests

4.906a 2 .0865.221 2 .074

.089 1 .765

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 14.04.

a.

Symmetric Measures

.136 .086

.136 .086266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

Did you work before

Missing

Yes

No

Gender * Every day I attend a place of worship and then go home

Crosstab

Count

37 25 21 8378 72 33 183

115 97 54 266

MaleFemale

Gender

Total

Missing Yes No

Every day I attend a place of worshipand then go home

Total

Chi-Square Tests

2.869a 2 .2382.860 2 .239

.004 1 .950

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 16.85.

a.

Symmetric Measures

.104 .238

.104 .238266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

90

80

70

60

50

40

30

20

10

Every day I attend a

Missing

Yes

No

Gender * Every day I stay at homeCrosstab

Count

14 48 21 8348 107 28 18362 155 49 266

MaleFemale

Gender

Total

Missing Yes NoEvery day I stay at home

Total

Chi-Square Tests

5.251a 2 .0725.219 2 .074

4.092 1 .043

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 15.29.

a.

Symmetric Measures

.141 .072

.141 .072266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

Every day I stay at

Missing

Yes

No

Gender * Every day I visit my children/ relatives/ friends

Crosstab

Count

31 43 9 8349 108 26 18380 151 35 266

MaleFemale

Gender

Total

Missing Yes No

Every day I visit my children/relatives/ friends

Total

Chi-Square Tests

3.137a 2 .2083.084 2 .214

3.120 1 .077

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 10.92.

a.

Symmetric Measures

.109 .208

.109 .208266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

Every day I visit my

Missing

Yes

No

Gender * Every day I visit / Restaurants / entertainmentCrosstab

Count

39 15 29 8391 39 53 183

130 54 82 266

MaleFemale

Gender

Total

Missing Yes No

Every day I visit / Restaurants /entertainment

Total

Chi-Square Tests

1.045a 2 .5931.037 2 .595

.341 1 .560

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 16.85.

a.

Symmetric Measures

.063 .593

.063 .593266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

Every day I visit /

Missing

Yes

No

Gender * I am given assistance and support byCrosstab

Count

14 1 12 1 1 54 8332 0 22 6 2 121 18346 1 34 7 3 175 266

MaleFemale

Gender

Total

Missing .00

Localauthority

home carers

24-hoursprivate home

carers

Day carecentre for

elderly peopleI have no help

by others

I am given assistance and support by

Total

Chi-Square Tests

3.432a 5 .6343.693 5 .594

.021 1 .886

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

6 cells (50.0%) have expected count less than 5. Theminimum expected count is .31.

a.

Symmetric Measures

.114 .634

.114 .634266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

140

120

100

80

60

40

20

0

I am given assistanc

Missing

.00

Local authority home

carers

24-hours private hom

e carers

Day care centre for

elderly people

I have no help by ot

hers

Gender * I need help with shoppingCrosstab

Count

20 13 50 8343 48 92 18363 61 142 266

MaleFemale

Gender

Total

Missing Yes NoI need help with shopping

Total

Chi-Square Tests

3.852a 2 .1464.032 2 .133

.144 1 .704

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 19.03.

a.

Symmetric Measures

.120 .146

.120 .146266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I need help with sho

Missing

Yes

No

Gender * I need help with cleaningCrosstab

Count

18 18 47 8346 26 111 18364 44 158 266

MaleFemale

Gender

Total

Missing Yes NoI need help with cleaning

Total

Chi-Square Tests

2.369a 2 .3062.287 2 .319

.083 1 .773

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 13.73.

a.

Symmetric Measures

.094 .306

.094 .306266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I need help with cle

Missing

Yes

No

Gender * I need help with cleaning my houseCrosstab

Count

18 18 47 8342 50 91 18360 68 138 266

MaleFemale

Gender

Total

Missing Yes NoI need help with cleaning my house

Total

Chi-Square Tests

1.274a 2 .5291.288 2 .525

.258 1 .612

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 18.72.

a.

Symmetric Measures

.069 .529

.069 .529266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I need help with cle

Missing

Yes

No

Gender * I need help with personal care (bathroom, toilet,...)Crosstab

Count

19 7 57 8348 19 116 18367 26 173 266

MaleFemale

Gender

Total

Missing Yes No

I need help with personal care(bathroom, toilet,...)

Total

Chi-Square Tests

.720a 2 .698

.728 2 .695

.458 1 .498

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 8.11.

a.

Symmetric Measures

.052 .698

.052 .698266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

140

120

100

80

60

40

20

0

I need help with per

Missing

Yes

No

Gender * I need help with nursing careCrosstab

Count

19 5 59 8349 28 106 18368 33 165 266

MaleFemale

Gender

Total

Missing Yes NoI need help with nursing care

Total

Chi-Square Tests

5.892a 2 .0536.419 2 .040

1.208 1 .272

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 10.30.

a.

Symmetric Measures

.149 .053

.149 .053266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I need help with nur

Missing

Yes

No

Gender * I need help to arrange my personal affairs (bank, servises)

Crosstab

Count

21 13 49 8349 43 91 18370 56 140 266

MaleFemale

Gender

Total

Missing Yes No

I need help to arrange my personalaffairs (bank, servises)

Total

Chi-Square Tests

2.652a 2 .2652.727 2 .256

.380 1 .538

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 17.47.

a.

Symmetric Measures

.100 .265

.100 .265266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I need help to arran

Missing

Yes

No

Gender * I need help with transport to doctor or to hospitalCrosstab

Count

20 11 52 8341 51 91 18361 62 143 266

MaleFemale

Gender

Total

Missing Yes No

I need help with transport to doctoror to hospital

Total

Chi-Square Tests

7.079a 2 .0297.604 2 .022

.136 1 .712

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 19.03.

a.

Symmetric Measures

.163 .029

.163 .029266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I need help with tra

Missing

Yes

No

Gender * I need help with lonliness (I need company)Crosstab

Count

18 17 48 8346 45 92 18364 62 140 266

MaleFemale

Gender

Total

Missing Yes No

I need help with lonliness (I needcompany)

Total

Chi-Square Tests

1.316a 2 .5181.321 2 .517

.687 1 .407

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 19.35.

a.

Symmetric Measures

.070 .518

.070 .518266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I need help with lon

Missing

Yes

No

Gender * I need help to take care about my petCrosstab

Count

22 4 57 8357 8 118 18379 12 175 266

MaleFemale

Gender

Total

Missing Yes No

I need help to take care about mypet

Total

Chi-Square Tests

.592a 2 .744

.600 2 .741

.570 1 .450

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

1 cells (16.7%) have expected count less than 5. Theminimum expected count is 3.74.

a.

Symmetric Measures

.047 .744

.047 .744266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

140

120

100

80

60

40

20

0

I need help to take

Missing

Yes

No

Gender * I feel lonely

Crosstab

Count

20 32 11 9 7 4 8341 47 37 12 28 18 18361 79 48 21 35 22 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I feel lonely

Total

Chi-Square Tests

9.904a 5 .07810.138 5 .071

2.250 1 .134

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 6.55.

a.

Symmetric Measures

.193 .078

.193 .078266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

50

40

30

20

10

0

I feel lonely

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * I am satisfied with my lifeCrosstab

Count

11 5 4 10 25 28 8326 10 12 23 67 45 18337 15 16 33 92 73 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I am satisfied with my life

Total

Chi-Square Tests

2.804a 5 .7302.772 5 .735

.323 1 .570

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

2 cells (16.7%) have expected count less than 5. Theminimum expected count is 4.68.

a.

Symmetric Measures

.103 .730

.103 .730266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

70

60

50

40

30

20

10

0

I am satisfied with

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * I feel that my family cares about meCrosstab

Count

14 2 1 2 28 36 8323 8 4 7 61 80 18337 10 5 9 89 116 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I feel that my family cares about me

Total

Chi-Square Tests

1.978a 5 .8522.050 5 .842

.292 1 .589

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

4 cells (33.3%) have expected count less than 5. Theminimum expected count is 1.56.

a.

Symmetric Measures

.086 .852

.086 .852266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I feel that my famil

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * Is there a Voluntary Organisation for support for Elder people in your city?

Crosstab

Count

13 29 41 8334 67 82 18347 96 123 266

MaleFemale

Gender

Total

Missing Yes No

Is there a Voluntary Organisation forsupport for Elder people in your city?

Total

Chi-Square Tests

.579a 2 .749

.583 2 .747

.494 1 .482

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 14.67.

a.

Symmetric Measures

.047 .749

.047 .749266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

Is there a Voluntary

Missing

Yes

No

Gender * Are you interested in developing of the idea to establish a Centre for Elder people?

Crosstab

Count

16 49 18 8330 125 28 18346 174 46 266

MaleFemale

Gender

Total

Missing Yes No

Are you interested in developing ofthe idea to establish a Centre for

Elder people?Total

Chi-Square Tests

2.371a 2 .3062.328 2 .312

.018 1 .893

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 14.35.

a.

Symmetric Measures

.094 .306

.094 .306266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

140

120

100

80

60

40

20

0

Are you interested i

Missing

Yes

No

Gender * Are there enough opportunities for entertainment and participating in activities in your area?

Crosstab

Count

18 21 44 8327 46 110 18345 67 154 266

MaleFemale

Gender

Total

Missing Yes No

Are there enough opportunities forentertainment and participating in

activities in your area?Total

Chi-Square Tests

2.120a 2 .3472.059 2 .357

2.112 1 .146

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 14.04.

a.

Symmetric Measures

.089 .347

.089 .347266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

Are there enough opp

Missing

Yes

No

Gender * A centre for older people I would like to offer to me a better health care

Crosstab

Count

11 4 1 6 29 32 8315 7 3 9 68 81 18326 11 4 15 97 113 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me a better health care

Total

Chi-Square Tests

2.758a 5 .7372.666 5 .751

2.170 1 .141

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

4 cells (33.3%) have expected count less than 5. Theminimum expected count is 1.25.

a.

Symmetric Measures

.102 .737

.102 .737266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * A centre for older people I would like to offer to me lectures/presentations related to popular interests

Crosstab

Count

19 3 2 19 18 22 8340 2 7 30 62 42 18359 5 9 49 80 64 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me lectures/presentationsrelated to popular interests

Total

Chi-Square Tests

6.729a 5 .2426.694 5 .244

.162 1 .687

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

3 cells (25.0%) have expected count less than 5. Theminimum expected count is 1.56.

a.

Symmetric Measures

.159 .242

.159 .242266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * A centre for older people I would like to offer to me visits/trips

Crosstab

Count

16 2 5 9 26 25 8329 3 10 15 66 60 18345 5 15 24 92 85 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me visits/trips

Total

Chi-Square Tests

1.550a 5 .9071.527 5 .910

.818 1 .366

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

3 cells (25.0%) have expected count less than 5. Theminimum expected count is 1.56.

a.

Symmetric Measures

.076 .907

.076 .907266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * A centre for older people I would like to offer to me entertainment opportunities

Crosstab

Count

19 2 4 10 14 34 8340 4 8 19 44 68 18359 6 12 29 58 102 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me entertainment opportunities

Total

Chi-Square Tests

1.775a 5 .8791.835 5 .871

.024 1 .876

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

3 cells (25.0%) have expected count less than 5. Theminimum expected count is 1.87.

a.

Symmetric Measures

.082 .879

.082 .879266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

60

40

20

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * A centre for older people I would like to offer to me opportunities for increasing activities

Crosstab

Count

16 3 0 10 26 28 8344 3 6 15 57 58 18360 6 6 25 83 86 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me opportunities for increasingactivities

Total

Chi-Square Tests

5.259a 5 .3856.931 5 .226

.586 1 .444

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

4 cells (33.3%) have expected count less than 5. Theminimum expected count is 1.87.

a.

Symmetric Measures

.141 .385

.141 .385266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * A centre for older people I would like to offer to me food

Crosstab

Count

21 6 5 15 17 19 8356 5 17 22 47 36 18377 11 22 37 64 55 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me food

Total

Chi-Square Tests

6.513a 5 .2596.284 5 .280

.361 1 .548

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

1 cells (8.3%) have expected count less than 5. Theminimum expected count is 3.43.

a.

Symmetric Measures

.156 .259

.156 .259266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

60

50

40

30

20

10

0

A centre for older p

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * Elderly people don't need lectures, theatrical plays and trips, they only need caring and food.

Crosstab

Count

12 20 25 10 11 5 8318 71 58 13 15 8 18330 91 83 23 26 13 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Elderly people don't need lectures, theatrical plays and trips, they only needcaring and food.

Total

Chi-Square Tests

8.161a 5 .1488.180 5 .147

.511 1 .475

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

1 cells (8.3%) have expected count less than 5. Theminimum expected count is 4.06.

a.

Symmetric Measures

.175 .148

.175 .148266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

60

40

20

0

Elderly people don't

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * Young people need good company more than elderly people.

Crosstab

Count

12 26 22 9 10 4 8322 58 63 14 20 6 18334 84 85 23 30 10 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Young people need good company more than elderly people.

Total

Chi-Square Tests

2.486a 5 .7792.477 5 .780

.001 1 .977

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

1 cells (8.3%) have expected count less than 5. Theminimum expected count is 3.12.

a.

Symmetric Measures

.097 .779

.097 .779266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

70

60

50

40

30

20

10

0

Young people need go

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * People, in spite of their age, want to learn and be active.

Crosstab

Count

12 2 3 15 22 29 8320 3 7 11 69 73 18332 5 10 26 91 102 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

People, in spite of their age, want to learn and be active.

Total

Chi-Square Tests

11.735a 5 .03911.059 5 .050

1.900 1 .168

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

3 cells (25.0%) have expected count less than 5. Theminimum expected count is 1.56.

a.

Symmetric Measures

.210 .039

.210 .039266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

60

40

20

0

People, in spite of

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * Elderly people can enjoy life as younger people do.

Crosstab

Count

12 4 4 4 33 26 8314 6 17 11 81 54 18326 10 21 15 114 80 266

MaleFemale

Gender

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Elderly people can enjoy life as younger people do.

Total

Chi-Square Tests

4.990a 5 .4174.947 5 .422

1.538 1 .215

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

2 cells (16.7%) have expected count less than 5. Theminimum expected count is 3.12.

a.

Symmetric Measures

.137 .417

.137 .417266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

Elderly people can e

Missing

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Gender * I would like computer lessonsCrosstab

Count

20 25 38 8349 30 104 18369 55 142 266

MaleFemale

Gender

Total

Missing Yes NoI would like computer lessons

Total

Chi-Square Tests

6.667a 2 .0366.386 2 .041

.018 1 .892

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 17.16.

a.

Symmetric Measures

.158 .036

.158 .036266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like compute

Missing

Yes

No

Gender * I would like cooking lessonsCrosstab

Count

23 12 48 8343 72 68 18366 84 116 266

MaleFemale

Gender

Total

Missing Yes NoI would like cooking lessons

Total

Chi-Square Tests

17.203a 2 .00018.638 2 .000

.143 1 .706

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 20.59.

a.

Symmetric Measures

.254 .000

.254 .000266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

80

70

60

50

40

30

20

10

0

I would like cooking

Missing

Yes

No

Gender * I would like dancing lessonsCrosstab

Count

21 14 48 8347 37 99 18368 51 147 266

MaleFemale

Gender

Total

Missing Yes NoI would like dancing lessons

Total

Chi-Square Tests

.482a 2 .786

.488 2 .783

.048 1 .826

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 15.91.

a.

Symmetric Measures

.043 .786

.043 .786266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like dancing

Missing

Yes

No

Gender * I would like art and crafts lessonsCrosstab

Count

20 11 52 8347 38 98 18367 49 150 266

MaleFemale

Gender

Total

Missing Yes NoI would like art and crafts lessons

Total

Chi-Square Tests

2.645a 2 .2672.739 2 .254

.391 1 .532

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 15.29.

a.

Symmetric Measures

.100 .267

.100 .267266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like art and

Missing

Yes

No

Gender * I would like pottery lessonsCrosstab

Count

21 9 53 8361 14 108 18382 23 161 266

MaleFemale

Gender

Total

Missing Yes NoI would like pottery lessons

Total

Chi-Square Tests

2.089a 2 .3522.105 2 .349

1.453 1 .228

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 7.18.

a.

Symmetric Measures

.089 .352

.089 .352266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like pottery

Missing

Yes

No

Gender * I would like foreing languages lessonsCrosstab

Count

21 12 50 8355 27 101 18376 39 151 266

MaleFemale

Gender

Total

Missing Yes No

I would like foreing languageslessons

Total

Chi-Square Tests

.711a 2 .701

.719 2 .698

.694 1 .405

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 12.17.

a.

Symmetric Measures

.052 .701

.052 .701266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like foreing

Missing

Yes

No

Gender * I would like my countries' language for foreignersCrosstab

Count

24 3 56 8360 14 109 18384 17 165 266

MaleFemale

Gender

Total

Missing Yes No

I would like my countries' languagefor foreigners

Total

Chi-Square Tests

2.302a 2 .3162.459 2 .293

.646 1 .422

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 5.30.

a.

Symmetric Measures

.093 .316

.093 .316266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

I would like my coun

Missing

Yes

No

Gender * I would like gymnastics lessonsCrosstab

Count

21 15 47 8353 36 94 18374 51 141 266

MaleFemale

Gender

Total

Missing Yes NoI would like gymnastics lessons

Total

Chi-Square Tests

.649a 2 .723

.651 2 .722

.510 1 .475

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 15.91.

a.

Symmetric Measures

.049 .723

.049 .723266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I would like gymnast

Missing

Yes

No

Gender * I would like fashion-embroidery lessonsCrosstab

Count

22 1 60 8350 41 92 18372 42 152 266

MaleFemale

Gender

Total

Missing Yes No

I would like fashion-embroiderylessons

Total

Chi-Square Tests

21.111a 2 .00028.208 2 .000

1.154 1 .283

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 13.11.

a.

Symmetric Measures

.282 .000

.282 .000266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I would like fashion

Missing

Yes

No

Gender * I would like discussion on a variety of topics

Crosstab

Count

14 44 25 8331 94 58 18345 138 83 266

MaleFemale

Gender

Total

Missing Yes No

I would like discussion on a varietyof topics

Total

Chi-Square Tests

.075a 2 .963

.075 2 .963

.006 1 .939

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 14.04.

a.

Symmetric Measures

.017 .963

.017 .963266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

I would like discuss

Missing

Yes

No

Gender * To participate in a team to publish a book with traditional recipes

Crosstab

Count

19 7 57 8346 56 81 18365 63 138 266

MaleFemale

Gender

Total

Missing Yes No

To participate in a team to publish abook with traditional recipes

Total

Chi-Square Tests

18.525a 2 .00020.608 2 .000

2.065 1 .151

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 19.66.

a.

Symmetric Measures

.264 .000

.264 .000266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

To participate in a

Missing

Yes

No

Gender * To participate in a team to publish a book with traditional myths and stories

Crosstab

Count

17 17 49 8358 25 100 18375 42 149 266

MaleFemale

Gender

Total

Missing Yes No

To participate in a team to publish abook with traditional myths and

storiesTotal

Chi-Square Tests

4.425a 2 .1094.503 2 .105

2.727 1 .099

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 13.11.

a.

Symmetric Measures

.129 .109

.129 .109266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

To participate in a

Missing

Yes

No

Gender * To participate in a team to publish a book with old pictures from our city or town

Crosstab

Count

16 27 40 8354 34 95 18370 61 135 266

MaleFemale

Gender

Total

Missing Yes No

To participate in a team to publish abook with old pictures from our city

or townTotal

Chi-Square Tests

7.273a 2 .0267.128 2 .028

1.480 1 .224

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 19.03.

a.

Symmetric Measures

.165 .026

.165 .026266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

100

80

60

40

20

0

To participate in a

Missing

Yes

No

Gender * To participate in a team to publish a tourist guide about our city or town

Crosstab

Count

19 17 47 8359 22 102 18378 39 149 266

MaleFemale

Gender

Total

Missing Yes No

To participate in a team to publish atourist guide about our city or town

Total

Chi-Square Tests

4.498a 2 .1064.422 2 .110

1.538 1 .215

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 12.17.

a.

Symmetric Measures

.130 .106

.130 .106266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

To participate in a

Missing

Yes

No

Gender * To participate in a team to publish a book with traditional songs

Crosstab

Count

17 20 46 8349 36 98 18366 56 144 266

MaleFemale

Gender

Total

Missing Yes No

To participate in a team to publish abook with traditional songs

Total

Chi-Square Tests

1.479a 2 .4771.499 2 .472

.896 1 .344

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

0 cells (.0%) have expected count less than 5. Theminimum expected count is 17.47.

a.

Symmetric Measures

.075 .477

.075 .477266

PhiCramer's V

Nominal byNominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the nullhypothesis.

b.

Gender

FemaleMale

Cou

nt

120

100

80

60

40

20

0

To participate in a

Missing

Yes

No

Crosstabs Country *All statements

Country *Age Crosstab

2 9 7 9 277.4 8.7 7.2 3.7 27.0

7.4% 33.3% 25.9% 33.3% 100.0%2.7% 10.5% 9.9% 25.0% 10.2%.8% 3.4% 2.6% 3.4% 10.2%-5.4 .3 -.2 5.3-2.0 .1 -.1 2.8-2.5 .1 -.1 3.2

10 13 15 5 4311.8 13.9 11.5 5.8 43.0

23.3% 30.2% 34.9% 11.6% 100.0%13.7% 15.1% 21.1% 13.9% 16.2%3.8% 4.9% 5.6% 1.9% 16.2%

-1.8 -.9 3.5 -.8-.5 -.2 1.0 -.3-.7 -.3 1.3 -.416 32 31 17 96

26.3 31.0 25.6 13.0 96.016.7% 33.3% 32.3% 17.7% 100.0%21.9% 37.2% 43.7% 47.2% 36.1%6.0% 12.0% 11.7% 6.4% 36.1%-10.3 1.0 5.4 4.0-2.0 .2 1.1 1.1-3.0 .3 1.6 1.5

45 31 18 5 9927.2 32.0 26.4 13.4 99.0

45.5% 31.3% 18.2% 5.1% 100.0%61.6% 36.0% 25.4% 13.9% 37.2%16.9% 11.7% 6.8% 1.9% 37.2%

17.8 -1.0 -8.4 -8.43.4 -.2 -1.6 -2.35.1 -.3 -2.4 -3.1

0 1 0 0 1.3 .3 .3 .1 1.0

.0% 100.0% .0% .0% 100.0%

.0% 1.2% .0% .0% .4%

.0% .4% .0% .0% .4%-.3 .7 -.3 -.1-.5 1.2 -.5 -.4-.6 1.4 -.6 -.473 86 71 36 266

73.0 86.0 71.0 36.0 266.027.4% 32.3% 26.7% 13.5% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0%27.4% 32.3% 26.7% 13.5% 100.0%

CountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

50-59 60-69 70-79 80+Age

Total

Crosstab

2 9 7 9 277.4 8.7 7.2 3.7 27.0

7.4% 33.3% 25.9% 33.3% 100.0%2.7% 10.5% 9.9% 25.0% 10.2%.8% 3.4% 2.6% 3.4% 10.2%-5.4 .3 -.2 5.3-2.0 .1 -.1 2.8-2.5 .1 -.1 3.2

10 13 15 5 4311.8 13.9 11.5 5.8 43.0

23.3% 30.2% 34.9% 11.6% 100.0%13.7% 15.1% 21.1% 13.9% 16.2%3.8% 4.9% 5.6% 1.9% 16.2%

-1.8 -.9 3.5 -.8-.5 -.2 1.0 -.3-.7 -.3 1.3 -.416 32 31 17 96

26.3 31.0 25.6 13.0 96.016.7% 33.3% 32.3% 17.7% 100.0%21.9% 37.2% 43.7% 47.2% 36.1%6.0% 12.0% 11.7% 6.4% 36.1%-10.3 1.0 5.4 4.0-2.0 .2 1.1 1.1-3.0 .3 1.6 1.5

45 31 18 5 9927.2 32.0 26.4 13.4 99.0

45.5% 31.3% 18.2% 5.1% 100.0%61.6% 36.0% 25.4% 13.9% 37.2%16.9% 11.7% 6.8% 1.9% 37.2%

17.8 -1.0 -8.4 -8.43.4 -.2 -1.6 -2.35.1 -.3 -2.4 -3.1

0 1 0 0 1.3 .3 .3 .1 1.0

.0% 100.0% .0% .0% 100.0%

.0% 1.2% .0% .0% .4%

.0% .4% .0% .0% .4%-.3 .7 -.3 -.1-.5 1.2 -.5 -.4-.6 1.4 -.6 -.473 86 71 36 266

73.0 86.0 71.0 36.0 266.027.4% 32.3% 26.7% 13.5% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0%27.4% 32.3% 26.7% 13.5% 100.0%

CountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Age% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

50-59 60-69 70-79 80+Age

Total

Chi-Square Tests

41.548a 12 .00041.537 12 .000

24.191 1 .000

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (25.0%) have expected count less than 5. The minimumexpected count is .14.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.121 .047 2.452 .014

.156 .064 2.268 .023

.089 .054 1.576 .115

.060 .019 .000c

.048 .015 .000c

.059 .017 3.401 .000d

.061 .018 3.401 .000d

.058 .017 3.401 .000d

.271 .049 5.538 .000

.264 .047 5.538 .000

.278 .050 5.538 .000

.306

.357

SymmetricCountry DependentAge DependentCountry DependentAge DependentSymmetricCountry DependentAge DependentSymmetricCountry DependentAge DependentCountry DependentAge Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.395 .000

.228 .000

.368 .000

.271 .049 5.538 .000

.257 .046 5.538 .000

.372 .065 5.538 .000

.317 .056 5.424 .000c

.302 .056 5.150 .000c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Age

50-59

60-69

70-79

80+

Country * Nationality

Crosstab

27 0 2725.3 1.7 27.0

100.0% .0% 100.0%10.8% .0% 10.2%10.2% .0% 10.2%

1.7 -1.7.3 -1.3

1.4 -1.441 2 43

40.3 2.7 43.095.3% 4.7% 100.0%16.5% 11.8% 16.2%15.4% .8% 16.2%

.7 -.7

.1 -.5

.5 -.593 3 96

89.9 6.1 96.096.9% 3.1% 100.0%37.3% 17.6% 36.1%35.0% 1.1% 36.1%

3.1 -3.1.3 -1.3

1.6 -1.688 11 99

92.7 6.3 99.088.9% 11.1% 100.0%35.3% 64.7% 37.2%33.1% 4.1% 37.2%

-4.7 4.7-.5 1.9

-2.4 2.40 1 1

.9 .1 1.0.0% 100.0% 100.0%.0% 5.9% .4%.0% .4% .4%

-.9 .9-1.0 3.7-3.8 3.8249 17 266

249.0 17.0 266.093.6% 6.4% 100.0%

100.0% 100.0% 100.0%93.6% 6.4% 100.0%

CountExpected Count% within Country% within Nationality% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Nationality% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Nationality% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Nationality% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Nationality% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Nationality% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Local OtherNationality

Total

Chi-Square Tests

22.107a 4 .00014.453 4 .006

7.570 1 .006

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (40.0%) have expected count less than 5. The minimumexpected count is .06.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.033 .072 .445 .656

.030 .079 .372 .710

.059 .057 1.002 .316

.012 .009 .011c

.083 .018 .000c

.036 .017 2.008 .006d

.021 .010 2.008 .006d

.114 .053 2.008 .006d

-.115 .037 -2.671 .008-.390 .119 -2.671 .008-.067 .025 -2.671 .008.169.288

SymmetricCountry DependentNationality DependentCountry DependentNationality DependentSymmetricCountry DependentNationality DependentSymmetricCountry DependentNationality DependentCountry DependentNationality Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.288 .000

.288 .000

.277 .000-.162 .052 -2.671 .008-.093 .035 -2.671 .008-.569 .174 -2.671 .008

-.175 .056 -2.882 .004c

-.169 .051 -2.786 .006c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus.00

Cou

nt

100

80

60

40

20

0

Nationality

Local

Other

Country * Studies

Crosstab

0 0 1 13 5 8 27.2 5.2 7.4 6.5 4.8 2.9 27.0

.0% .0% 3.7% 48.1% 18.5% 29.6% 100.0%

.0% .0% 1.4% 20.3% 10.6% 27.6% 10.2%

.0% .0% .4% 4.9% 1.9% 3.0% 10.2%-.2 -5.2 -6.4 6.5 .2 5.1-.5 -2.3 -2.4 2.6 .1 2.9-.5 -2.7 -2.9 3.1 .1 3.3

0 5 12 11 10 5 43.3 8.2 11.8 10.3 7.6 4.7 43.0

.0% 11.6% 27.9% 25.6% 23.3% 11.6% 100.0%

.0% 9.8% 16.4% 17.2% 21.3% 17.2% 16.2%

.0% 1.9% 4.5% 4.1% 3.8% 1.9% 16.2%-.3 -3.2 .2 .7 2.4 .3-.6 -1.1 .1 .2 .9 .1-.6 -1.4 .1 .3 1.0 .2

0 20 20 30 22 4 96.7 18.4 26.3 23.1 17.0 10.5 96.0

.0% 20.8% 20.8% 31.3% 22.9% 4.2% 100.0%

.0% 39.2% 27.4% 46.9% 46.8% 13.8% 36.1%

.0% 7.5% 7.5% 11.3% 8.3% 1.5% 36.1%-.7 1.6 -6.3 6.9 5.0 -6.5-.8 .4 -1.2 1.4 1.2 -2.0

-1.1 .5 -1.8 2.1 1.7 -2.62 26 40 10 10 11 99

.7 19.0 27.2 23.8 17.5 10.8 99.02.0% 26.3% 40.4% 10.1% 10.1% 11.1% 100.0%

100.0% 51.0% 54.8% 15.6% 21.3% 37.9% 37.2%.8% 9.8% 15.0% 3.8% 3.8% 4.1% 37.2%1.3 7.0 12.8 -13.8 -7.5 .21.5 1.6 2.5 -2.8 -1.8 .11.8 2.3 3.6 -4.1 -2.5 .1

0 0 0 0 0 1 1.0 .2 .3 .2 .2 .1 1.0

.0% .0% .0% .0% .0% 100.0% 100.0%

.0% .0% .0% .0% .0% 3.4% .4%

.0% .0% .0% .0% .0% .4% .4%.0 -.2 -.3 -.2 -.2 .9

-.1 -.4 -.5 -.5 -.4 2.7-.1 -.5 -.6 -.6 -.5 2.9

2 51 73 64 47 29 2662.0 51.0 73.0 64.0 47.0 29.0 266.0

.8% 19.2% 27.4% 24.1% 17.7% 10.9% 100.0%100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

.8% 19.2% 27.4% 24.1% 17.7% 10.9% 100.0%

CountExpected Count% within Country% within Studies% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Studies% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Studies% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Studies% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Studies% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Studies% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing

I only studiedfew classes in

PrimarySchool

I graduatedfrom Primary

School

I graduatedfrom

SecondarySchool

I graduatedfrom Lyceum

(Higherschool) (FE)

I graduatedfrom

college/university (HE)

Studies

Total

Chi-Square Tests

68.676a 20 .00072.687 20 .000

23.667 1 .000

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

13 cells (43.3%) have expected count less than 5. The minimumexpected count is .01.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.153 .036 4.037 .000

.192 .046 3.876 .000

.119 .039 2.897 .004

.080 .019 .000c

.061 .012 .000c

.095 .018 5.121 .000d

.106 .020 5.121 .000d

.085 .017 5.121 .000d

.250 .050 4.996 .000

.235 .047 4.996 .000

.266 .053 4.996 .000

.374

.340

SymmetricCountry DependentStudies DependentCountry DependentStudies DependentSymmetricCountry DependentStudies DependentSymmetricCountry DependentStudies DependentCountry DependentStudies Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.508 .000

.254 .000

.453 .000

.250 .050 4.996 .000

.231 .046 4.996 .000

.331 .065 4.996 .000

.296 .059 5.042 .000c

.299 .057 5.088 .000c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Co

un

t

50

40

30

20

10

0

Studies

I only studied few c

lasses in Primary Sc

I graduated from Pri

mary School

I graduated from Sec

ondary School

I graduated from Lyc

eum (Higher school)

I graduated from col

lege/university (HE)

Country * Living conditions

Crosstab

0 17 10 0 27.4 9.3 17.2 .1 27.0

.0% 63.0% 37.0% .0% 100.0%

.0% 18.5% 5.9% .0% 10.2%

.0% 6.4% 3.8% .0% 10.2%-.4 7.7 -7.2 -.1-.6 2.5 -1.7 -.3-.7 3.3 -3.0 -.3

0 12 30 1 43.6 14.9 27.3 .2 43.0

.0% 27.9% 69.8% 2.3% 100.0%

.0% 13.0% 17.8% 100.0% 16.2%

.0% 4.5% 11.3% .4% 16.2%-.6 -2.9 2.7 .8-.8 -.7 .5 2.1-.9 -1.0 .9 2.3

4 32 60 0 961.4 33.2 61.0 .4 96.0

4.2% 33.3% 62.5% .0% 100.0%100.0% 34.8% 35.5% .0% 36.1%

1.5% 12.0% 22.6% .0% 36.1%2.6 -1.2 -1.0 -.42.1 -.2 -.1 -.62.7 -.3 -.3 -.8

0 31 68 0 991.5 34.2 62.9 .4 99.0

.0% 31.3% 68.7% .0% 100.0%

.0% 33.7% 40.2% .0% 37.2%

.0% 11.7% 25.6% .0% 37.2%-1.5 -3.2 5.1 -.4-1.2 -.6 .6 -.6-1.6 -.9 1.3 -.8

0 0 1 0 1.0 .3 .6 .0 1.0

.0% .0% 100.0% .0% 100.0%

.0% .0% .6% .0% .4%

.0% .0% .4% .0% .4%.0 -.3 .4 .0

-.1 -.6 .5 -.1-.1 -.7 .8 -.1

4 92 169 1 2664.0 92.0 169.0 1.0 266.0

1.5% 34.6% 63.5% .4% 100.0%100.0% 100.0% 100.0% 100.0% 100.0%

1.5% 34.6% 63.5% .4% 100.0%

CountExpected Count% within Country% within Living conditions% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Living conditions% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Living conditions% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Living conditions% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Living conditions% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Living conditions% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No 3.00Living conditions

Total

Chi-Square Tests

23.692a 12 .02222.857 12 .029

2.231 1 .135

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

12 cells (60.0%) have expected count less than 5. The minimumexpected count is .00.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.049 .036 1.338 .181

.036 .048 .728 .466

.072 .052 1.352 .176

.025 .005 .008c

.041 .023 .001c

.042 .015 2.709 .029d

.033 .012 2.709 .029d

.058 .020 2.709 .029d

-.094 .055 -1.718 .086-.115 .067 -1.718 .086

-.079 .046 -1.718 .086

.151

.192

SymmetricCountry DependentLiving conditionsDependentCountry DependentLiving conditionsDependentSymmetricCountry DependentLiving conditionsDependentSymmetricCountry DependentLiving conditionsDependentCountry DependentLiving conditionsDependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.298 .022

.172 .022

.286 .022-.096 .056 -1.718 .086-.073 .043 -1.718 .086-.164 .094 -1.718 .086

-.104 .061 -1.705 .089c

-.092 .047 -1.497 .136c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

Living conditions

Yes

No

3.00

Country * With whom do you live?

Crosstab

17 5 2 1 2 277.6 10.7 3.6 4.3 .9 27.0

63.0% 18.5% 7.4% 3.7% 7.4% 100.0%

22.7% 4.8% 5.7% 2.4% 22.2% 10.2%

6.4% 1.9% .8% .4% .8% 10.2%9.4 -5.7 -1.6 -3.3 1.13.4 -1.7 -.8 -1.6 1.14.2 -2.4 -.9 -1.8 1.212 11 5 14 1 43

12.1 17.0 5.7 6.8 1.5 43.027.9% 25.6% 11.6% 32.6% 2.3% 100.0%

16.0% 10.5% 14.3% 33.3% 11.1% 16.2%

4.5% 4.1% 1.9% 5.3% .4% 16.2%-.1 -6.0 -.7 7.2 -.5.0 -1.4 -.3 2.8 -.4.0 -2.0 -.3 3.3 -.429 38 23 4 2 96

27.1 37.9 12.6 15.2 3.2 96.030.2% 39.6% 24.0% 4.2% 2.1% 100.0%

38.7% 36.2% 65.7% 9.5% 22.2% 36.1%

10.9% 14.3% 8.6% 1.5% .8% 36.1%1.9 .1 10.4 -11.2 -1.2.4 .0 2.9 -2.9 -.7.5 .0 3.9 -3.9 -.916 51 5 23 4 99

27.9 39.1 13.0 15.6 3.3 99.016.2% 51.5% 5.1% 23.2% 4.0% 100.0%

21.3% 48.6% 14.3% 54.8% 44.4% 37.2%

6.0% 19.2% 1.9% 8.6% 1.5% 37.2%-11.9 11.9 -8.0 7.4 .7-2.3 1.9 -2.2 1.9 .4-3.4 3.1 -3.0 2.6 .5

1 0 0 0 0 1.3 .4 .1 .2 .0 1.0

100.0% .0% .0% .0% .0% 100.0%

1.3% .0% .0% .0% .0% .4%

.4% .0% .0% .0% .0% .4%.7 -.4 -.1 -.2 .0

1.4 -.6 -.4 -.4 -.21.6 -.8 -.4 -.4 -.275 105 35 42 9 266

75.0 105.0 35.0 42.0 9.0 266.028.2% 39.5% 13.2% 15.8% 3.4% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

28.2% 39.5% 13.2% 15.8% 3.4% 100.0%

CountExpected Count% within Country% within Withwhom do you live?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Withwhom do you live?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Withwhom do you live?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Withwhom do you live?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Withwhom do you live?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Withwhom do you live?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing

With myhusband/wife/partner

With mychildren

With myhusband/wife/partner andmy children

With otherpeople

With whom do you live?

Total

Chi-Square Tests

66.182a 16 .00066.840 16 .000

9.480 1 .002

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

11 cells (44.0%) have expected count less than 5. The minimumexpected count is .03.

a.

Both variables must have identical values of categories.b.

Directional Measures

.143 .030 4.427 .000

.186 .046 3.722 .000

.099 .041 2.333 .020

.088 .020 .000c

.074 .018 .000c

.094 .021 4.406 .000d

.098 .022 4.406 .000d

.090 .020 4.406 .000d

-.115 .057 -2.021 .043-.113 .056 -2.021 .043

-.117 .058 -2.021 .043

.286

.285

SymmetricCountry DependentWith whom do youlive? DependentCountry DependentWith whom do youlive? DependentSymmetricCountry DependentWith whom do youlive? DependentSymmetricCountry DependentWith whom do youlive? DependentCountry DependentWith whom do youlive? Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.499 .000

.249 .000

.446 .000-.115 .057 -2.021 .043-.102 .050 -2.021 .043-.157 .078 -2.021 .043

-.138 .065 -2.269 .024c

-.189 .066 -3.130 .002c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

With whom do you liv

With my husband/w ife

/partner

With my children

With my husband/w ife

/partner and my chil

With other people

Country * Are you in employment?

Crosstab

0 9 18 27.4 5.7 20.9 27.0

.0% 33.3% 66.7% 100.0%

.0% 16.1% 8.7% 10.2%

.0% 3.4% 6.8% 10.2%-.4 3.3 -2.9-.6 1.4 -.6-.7 1.7 -1.4

0 4 39 43.6 9.1 33.3 43.0

.0% 9.3% 90.7% 100.0%

.0% 7.1% 18.9% 16.2%

.0% 1.5% 14.7% 16.2%-.6 -5.1 5.7-.8 -1.7 1.0-.9 -2.1 2.3

1 24 71 961.4 20.2 74.3 96.0

1.0% 25.0% 74.0% 100.0%

25.0% 42.9% 34.5% 36.1%

.4% 9.0% 26.7% 36.1%-.4 3.8 -3.3-.4 .8 -.4-.5 1.2 -1.0

3 19 77 991.5 20.8 76.7 99.0

3.0% 19.2% 77.8% 100.0%

75.0% 33.9% 37.4% 37.2%

1.1% 7.1% 28.9% 37.2%1.5 -1.8 .31.2 -.4 .01.6 -.6 .1

0 0 1 1.0 .2 .8 1.0

.0% .0% 100.0% 100.0%

.0% .0% .5% .4%

.0% .0% .4% .4%.0 -.2 .2

-.1 -.5 .3-.1 -.5 .5

4 56 206 2664.0 56.0 206.0 266.0

1.5% 21.1% 77.4% 100.0%

100.0% 100.0% 100.0% 100.0%

1.5% 21.1% 77.4% 100.0%

CountExpected Count% within Country% within Are you inemployment?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are you inemployment?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are you inemployment?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are you inemployment?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are you inemployment?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are you inemployment?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoAre you in employment?

Total

Chi-Square Tests

10.174a 8 .25311.503 8 .175

.651 1 .420

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

7 cells (46.7%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.022 .029 .763 .445

.030 .039 .763 .445

.000 .000 .c

.c

.011 .007 .179d

.027 .017 .081d

.023 .012 1.971 .175e

.017 .008 1.971 .175e

.037 .018 1.971 .175e

.009 .053 .159 .873

.013 .079 .159 .873

.006 .040 .159 .873

.098

.132

SymmetricCountry DependentAre you in employment?DependentCountry DependentAre you in employment?DependentSymmetricCountry DependentAre you in employment?DependentSymmetricCountry DependentAre you in employment?DependentCountry DependentAre you in employment?Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Symmetric Measures

.196 .253

.138 .253

.192 .253

.009 .056 .159 .873

.007 .042 .159 .873

.018 .114 .159 .873

.010 .061 .158 .875c

.050 .054 .806 .421c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

Are you in employmen

Yes

No

Country * Did you work before your retirement?

Crosstab

4 17 6 274.6 17.6 4.9 27.0

14.8% 63.0% 22.2% 100.0%

8.9% 9.8% 12.5% 10.2%

1.5% 6.4% 2.3% 10.2%-.6 -.6 1.1-.3 -.1 .5-.3 -.2 .6

1 37 5 437.3 28.0 7.8 43.0

2.3% 86.0% 11.6% 100.0%

2.2% 21.4% 10.4% 16.2%

.4% 13.9% 1.9% 16.2%-6.3 9.0 -2.8-2.3 1.7 -1.0-2.8 3.2 -1.2

15 64 17 9616.2 62.4 17.3 96.0

15.6% 66.7% 17.7% 100.0%

33.3% 37.0% 35.4% 36.1%

5.6% 24.1% 6.4% 36.1%-1.2 1.6 -.3-.3 .2 -.1-.4 .4 -.125 54 20 99

16.7 64.4 17.9 99.025.3% 54.5% 20.2% 100.0%

55.6% 31.2% 41.7% 37.2%

9.4% 20.3% 7.5% 37.2%8.3 -10.4 2.12.0 -1.3 .52.8 -2.8 .7

0 1 0 1.2 .7 .2 1.0

.0% 100.0% .0% 100.0%

.0% .6% .0% .4%

.0% .4% .0% .4%-.2 .3 -.2-.4 .4 -.4-.5 .7 -.545 173 48 266

45.0 173.0 48.0 266.016.9% 65.0% 18.0% 100.0%

100.0% 100.0% 100.0% 100.0%

16.9% 65.0% 18.0% 100.0%

CountExpected Count% within Country% within Did you workbefore your retirement?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Did you workbefore your retirement?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Did you workbefore your retirement?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Did you workbefore your retirement?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Did you workbefore your retirement?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Did you workbefore your retirement?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Did you work before yourretirement?

Total

Chi-Square Tests

16.335a 8 .03819.233 8 .014

4.692 1 .030

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (33.3%) have expected count less than 5. The minimumexpected count is .17.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.038 .041 .922 .357

.060 .063 .922 .357

.000 .000 .c

.c

.021 .010 .005d

.037 .015 .011d

.033 .013 2.564 .014e

.028 .011 2.564 .014e

.041 .016 2.564 .014e

.078 .055 1.423 .155

.092 .064 1.423 .155

.068 .048 1.423 .155

.167

.166

SymmetricCountry DependentDid you work before yourretirement? DependentCountry DependentDid you work before yourretirement? DependentSymmetricCountry DependentDid you work before yourretirement? DependentSymmetricCountry DependentDid you work before yourretirement? DependentCountry DependentDid you work before yourretirement? Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Symmetric Measures

.248 .038

.175 .038

.241 .038

.079 .055 1.423 .155

.071 .050 1.423 .155

.133 .093 1.423 .155

.088 .062 1.440 .151c

.133 .059 2.181 .030c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

Did you work before

Yes

No

Country * Every day I attend a place of worship and then go home

Crosstab

18 3 6 2711.7 9.8 5.5 27.0

66.7% 11.1% 22.2% 100.0%

15.7% 3.1% 11.1% 10.2%

6.8% 1.1% 2.3% 10.2%6.3 -6.8 .51.9 -2.2 .22.6 -2.9 .3

0 21 22 4318.6 15.7 8.7 43.0.0% 48.8% 51.2% 100.0%

.0% 21.6% 40.7% 16.2%

.0% 7.9% 8.3% 16.2%-18.6 5.3 13.3-4.3 1.3 4.5-6.3 1.8 5.5

45 39 12 9641.5 35.0 19.5 96.0

46.9% 40.6% 12.5% 100.0%

39.1% 40.2% 22.2% 36.1%

16.9% 14.7% 4.5% 36.1%3.5 4.0 -7.5.5 .7 -1.7.9 1.1 -2.452 34 13 99

42.8 36.1 20.1 99.052.5% 34.3% 13.1% 100.0%

45.2% 35.1% 24.1% 37.2%

19.5% 12.8% 4.9% 37.2%9.2 -2.1 -7.11.4 -.3 -1.62.4 -.6 -2.2

0 0 1 1.4 .4 .2 1.0

.0% .0% 100.0% 100.0%

.0% .0% 1.9% .4%

.0% .0% .4% .4%-.4 -.4 .8-.7 -.6 1.8-.9 -.8 2.0

115 97 54 266115.0 97.0 54.0 266.0

43.2% 36.5% 20.3% 100.0%

100.0% 100.0% 100.0% 100.0%

43.2% 36.5% 20.3% 100.0%

CountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day I attenda place of worship andthen go home% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Every day I attend a place of worshipand then go home

Total

Chi-Square Tests

60.968a 8 .00074.582 8 .000

5.311 1 .021

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .20.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.116 .039 2.839 .005

.084 .060 1.352 .176

.152 .029 5.018 .000

.056 .014 .000c

.113 .016 .000c

.120 .018 6.424 .000d

.109 .016 6.424 .000d

.133 .021 6.424 .000d

.180 .057 3.152 .002

.187 .059 3.152 .002

.172 .055 3.152 .002

.192

.431

SymmetricCountry DependentEvery day I attend a placeof worship and then gohome DependentCountry DependentEvery day I attend a placeof worship and then gohome DependentSymmetricCountry DependentEvery day I attend a placeof worship and then gohome DependentSymmetricCountry DependentEvery day I attend a placeof worship and then gohome DependentCountry DependentEvery day I attend a placeof worship and then gohome Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.479 .000

.339 .000

.432 .000

.180 .057 3.152 .002

.180 .057 3.152 .002

.260 .081 3.152 .002

.197 .063 3.273 .001c

.142 .065 2.324 .021c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Every day I attend a

Yes

No

Country * Every day I stay at home

Crosstab

9 12 6 276.3 15.7 5.0 27.0

33.3% 44.4% 22.2% 100.0%

14.5% 7.7% 12.2% 10.2%

3.4% 4.5% 2.3% 10.2%2.7 -3.7 1.01.1 -.9 .51.3 -1.5 .5

0 18 25 4310.0 25.1 7.9 43.0.0% 41.9% 58.1% 100.0%

.0% 11.6% 51.0% 16.2%

.0% 6.8% 9.4% 16.2%-10.0 -7.1 17.1-3.2 -1.4 6.1-3.9 -2.4 7.3

18 72 6 9622.4 55.9 17.7 96.0

18.8% 75.0% 6.3% 100.0%

29.0% 46.5% 12.2% 36.1%

6.8% 27.1% 2.3% 36.1%-4.4 16.1 -11.7-.9 2.1 -2.8

-1.3 4.2 -3.835 53 11 99

23.1 57.7 18.2 99.035.4% 53.5% 11.1% 100.0%

56.5% 34.2% 22.4% 37.2%

13.2% 19.9% 4.1% 37.2%11.9 -4.7 -7.22.5 -.6 -1.73.6 -1.2 -2.4

0 0 1 1.2 .6 .2 1.0

.0% .0% 100.0% 100.0%

.0% .0% 2.0% .4%

.0% .0% .4% .4%-.2 -.6 .8-.5 -.8 1.9-.6 -1.2 2.162 155 49 266

62.0 155.0 49.0 266.023.3% 58.3% 18.4% 100.0%

100.0% 100.0% 100.0% 100.0%

23.3% 58.3% 18.4% 100.0%

CountExpected Count% within Country% within Every dayI stay at home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI stay at home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI stay at home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI stay at home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI stay at home% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI stay at home% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoEvery day I stay at home

Total

Chi-Square Tests

78.127a 8 .00075.728 8 .000

10.350 1 .001

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .18.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.147 .053 2.600 .009

.198 .068 2.634 .008

.072 .058 1.209 .227

.089 .023 .000c

.123 .029 .000c

.127 .024 5.041 .000d

.111 .021 5.041 .000d

.147 .028 5.041 .000d

.251 .058 4.239 .000

.278 .064 4.239 .000

.229 .054 4.239 .000

.260

.373

SymmetricCountry DependentEvery day I stay athome DependentCountry DependentEvery day I stay athome DependentSymmetricCountry DependentEvery day I stay athome DependentSymmetricCountry DependentEvery day I stay athome DependentCountry DependentEvery day I stay athome Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.542 .000

.383 .000

.476 .000

.252 .059 4.239 .000

.239 .056 4.239 .000

.378 .085 4.239 .000

.273 .065 4.615 .000c

.198 .066 3.276 .001c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

Every day I stay at

Yes

No

Country * Every day I visit my children/ relatives/ friends

Crosstab

9 14 4 278.1 15.3 3.6 27.0

33.3% 51.9% 14.8% 100.0%

11.3% 9.3% 11.4% 10.2%

3.4% 5.3% 1.5% 10.2%.9 -1.3 .4.3 -.3 .2.4 -.5 .30 30 13 43

12.9 24.4 5.7 43.0.0% 69.8% 30.2% 100.0%

.0% 19.9% 37.1% 16.2%

.0% 11.3% 4.9% 16.2%-12.9 5.6 7.3-3.6 1.1 3.1-4.7 1.9 3.6

47 37 12 9628.9 54.5 12.6 96.0

49.0% 38.5% 12.5% 100.0%

58.8% 24.5% 34.3% 36.1%

17.7% 13.9% 4.5% 36.1%18.1 -17.5 -.63.4 -2.4 -.25.0 -4.5 -.224 70 5 99

29.8 56.2 13.0 99.024.2% 70.7% 5.1% 100.0%

30.0% 46.4% 14.3% 37.2%

9.0% 26.3% 1.9% 37.2%-5.8 13.8 -8.0-1.1 1.8 -2.2-1.6 3.5 -3.0

0 0 1 1.3 .6 .1 1.0

.0% .0% 100.0% 100.0%

.0% .0% 2.9% .4%

.0% .0% .4% .4%-.3 -.6 .9-.5 -.8 2.4-.7 -1.1 2.680 151 35 266

80.0 151.0 35.0 266.030.1% 56.8% 13.2% 100.0%

100.0% 100.0% 100.0% 100.0%

30.1% 56.8% 13.2% 100.0%

CountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every dayI visit my children/relatives/ friends% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Every day I visit my children/relatives/ friends

Total

Chi-Square Tests

57.092a 8 .00065.060 8 .000

1.462 1 .227

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .13.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.149 .054 2.598 .009

.186 .051 3.355 .001

.096 .076 1.196 .232

.073 .020 .000c

.110 .025 .000c

.110 .020 5.385 .000d

.095 .017 5.385 .000d

.129 .023 5.385 .000d

.085 .051 1.665 .096

.095 .056 1.665 .096

.078 .046 1.665 .096

.165

.378

SymmetricCountry DependentEvery day I visit mychildren/ relatives/friends DependentCountry DependentEvery day I visit mychildren/ relatives/friends DependentSymmetricCountry DependentEvery day I visit mychildren/ relatives/friends DependentSymmetricCountry DependentEvery day I visit mychildren/ relatives/friends DependentCountry DependentEvery day I visit mychildren/ relatives/friends Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.463 .000

.328 .000

.420 .000

.086 .051 1.665 .096

.081 .049 1.665 .096

.130 .078 1.665 .096

.103 .058 1.682 .094c

.074 .058 1.210 .227c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

Every day I visit my

Yes

No

Country * Every day I visit / Restaurants / entertainment

Crosstab

12 10 5 2713.2 5.5 8.3 27.0

44.4% 37.0% 18.5% 100.0%

9.2% 18.5% 6.1% 10.2%

4.5% 3.8% 1.9% 10.2%-1.2 4.5 -3.3-.3 1.9 -1.2-.5 2.3 -1.5

0 4 39 4321.0 8.7 13.3 43.0.0% 9.3% 90.7% 100.0%

.0% 7.4% 47.6% 16.2%

.0% 1.5% 14.7% 16.2%-21.0 -4.7 25.7-4.6 -1.6 7.1-7.0 -2.0 9.3

64 11 21 9646.9 19.5 29.6 96.0

66.7% 11.5% 21.9% 100.0%

49.2% 20.4% 25.6% 36.1%

24.1% 4.1% 7.9% 36.1%17.1 -8.5 -8.62.5 -1.9 -1.64.4 -2.7 -2.454 29 16 99

48.4 20.1 30.5 99.054.5% 29.3% 16.2% 100.0%

41.5% 53.7% 19.5% 37.2%

20.3% 10.9% 6.0% 37.2%5.6 8.9 -14.5.8 2.0 -2.6

1.4 2.8 -4.00 0 1 1

.5 .2 .3 1.0.0% .0% 100.0% 100.0%

.0% .0% 1.2% .4%

.0% .0% .4% .4%-.5 -.2 .7-.7 -.5 1.2

-1.0 -.5 1.5130 54 82 266

130.0 54.0 82.0 266.048.9% 20.3% 30.8% 100.0%

100.0% 100.0% 100.0% 100.0%

48.9% 20.3% 30.8% 100.0%

CountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Every day Ivisit / Restaurants /entertainment% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Every day I visit / Restaurants /entertainment

Total

Chi-Square Tests

104.896a 8 .000110.151 8 .000

15.783 1 .000

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .20.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.241 .049 4.435 .000

.198 .071 2.539 .011

.294 .039 6.861 .000

.115 .024 .000c

.217 .027 .000c

.179 .026 6.763 .000d

.161 .023 6.763 .000d

.200 .030 6.763 .000d

.230 .050 4.556 .000

.243 .053 4.556 .000

.219 .047 4.556 .000

.274

.513

SymmetricCountry DependentEvery day I visit /Restaurants /entertainment DependentCountry DependentEvery day I visit /Restaurants /entertainment DependentSymmetricCountry DependentEvery day I visit /Restaurants /entertainment DependentSymmetricCountry DependentEvery day I visit /Restaurants /entertainment DependentCountry DependentEvery day I visit /Restaurants /entertainment Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.628 .000

.444 .000

.532 .000

.230 .050 4.556 .000

.228 .050 4.556 .000

.325 .069 4.556 .000

.276 .058 4.668 .000c

.244 .058 4.089 .000c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Every day I visit /

Yes

No

Country * I am given assistance and support by

Crosstab

4 1 7 3 0 12 274.7 .1 3.5 .7 .3 17.8 27.0

14.8% 3.7% 25.9% 11.1% .0% 44.4% 100.0%

8.7% 100.0% 20.6% 42.9% .0% 6.9% 10.2%

1.5% .4% 2.6% 1.1% .0% 4.5% 10.2%-.7 .9 3.5 2.3 -.3 -5.8-.3 2.8 1.9 2.7 -.6 -1.4-.4 3.0 2.2 2.9 -.6 -2.5

0 0 2 0 0 41 437.4 .2 5.5 1.1 .5 28.3 43.0

.0% .0% 4.7% .0% .0% 95.3% 100.0%

.0% .0% 5.9% .0% .0% 23.4% 16.2%

.0% .0% .8% .0% .0% 15.4% 16.2%-7.4 -.2 -3.5 -1.1 -.5 12.7-2.7 -.4 -1.5 -1.1 -.7 2.4-3.3 -.4 -1.7 -1.2 -.8 4.5

36 0 14 0 1 45 9616.6 .4 12.3 2.5 1.1 63.2 96.0

37.5% .0% 14.6% .0% 1.0% 46.9% 100.0%

78.3% .0% 41.2% .0% 33.3% 25.7% 36.1%

13.5% .0% 5.3% .0% .4% 16.9% 36.1%19.4 -.4 1.7 -2.5 -.1 -18.24.8 -.6 .5 -1.6 -.1 -2.36.5 -.8 .7 -2.0 -.1 -4.9

6 0 11 4 1 77 9917.1 .4 12.7 2.6 1.1 65.1 99.0

6.1% .0% 11.1% 4.0% 1.0% 77.8% 100.0%

13.0% .0% 32.4% 57.1% 33.3% 44.0% 37.2%

2.3% .0% 4.1% 1.5% .4% 28.9% 37.2%-11.1 -.4 -1.7 1.4 -.1 11.9-2.7 -.6 -.5 .9 -.1 1.5-3.7 -.8 -.6 1.1 -.1 3.2

0 0 0 0 1 0 1.2 .0 .1 .0 .0 .7 1.0

.0% .0% .0% .0% 100.0% .0% 100.0%

.0% .0% .0% .0% 33.3% .0% .4%

.0% .0% .0% .0% .4% .0% .4%-.2 .0 -.1 .0 1.0 -.7-.4 -.1 -.4 -.2 9.3 -.8-.5 -.1 -.4 -.2 9.4 -1.446 1 34 7 3 175 266

46.0 1.0 34.0 7.0 3.0 175.0 266.017.3% .4% 12.8% 2.6% 1.1% 65.8% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

17.3% .4% 12.8% 2.6% 1.1% 65.8% 100.0%

CountExpected Count% within Country% within I amgiven assistanceand support by% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amgiven assistanceand support by% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amgiven assistanceand support by% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amgiven assistanceand support by% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amgiven assistanceand support by% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amgiven assistanceand support by% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing .00

Localauthority

home carers

24-hoursprivate home

carers

Day carecentre for

elderly peopleI have no help

by others

I am given assistance and support by

Total

Chi-Square Tests

167.823a 20 .00089.902 20 .000

1.305 1 .253

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

20 cells (66.7%) have expected count less than 5. The minimumexpected count is .00.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.136 .029 4.232 .000

.204 .045 4.196 .000

.011 .011 1.002 .316

.111 .022 .000c

.137 .028 .000c

.147 .026 5.232 .000d

.132 .024 5.232 .000d

.167 .029 5.232 .000d

-.083 .047 -1.759 .079-.097 .055 -1.759 .079

-.073 .042 -1.759 .079

.190

.442

SymmetricCountry DependentI am given assistanceand support byDependentCountry DependentI am given assistanceand support byDependentSymmetricCountry DependentI am given assistanceand support byDependentSymmetricCountry DependentI am given assistanceand support byDependentCountry DependentI am given assistanceand support byDependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.794 .000

.397 .000

.622 .000-.084 .048 -1.759 .079-.063 .036 -1.759 .079-.134 .075 -1.759 .079

-.094 .056 -1.532 .127c

-.070 .051 -1.143 .254c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

I am given assistanc

Local authority home

carers

24-hours private hom

e carers

Day care centre for

elderly people

I have no help by ot

hers

Country * I need help with shopping

Crosstab

6 13 8 276.4 6.2 14.4 27.0

22.2% 48.1% 29.6% 100.0%

9.5% 21.3% 5.6% 10.2%

2.3% 4.9% 3.0% 10.2%-.4 6.8 -6.4-.2 2.7 -1.7-.2 3.3 -2.6

0 18 25 4310.2 9.9 23.0 43.0.0% 41.9% 58.1% 100.0%

.0% 29.5% 17.6% 16.2%

.0% 6.8% 9.4% 16.2%-10.2 8.1 2.0-3.2 2.6 .4-4.0 3.2 .7

41 17 38 9622.7 22.0 51.2 96.0

42.7% 17.7% 39.6% 100.0%

65.1% 27.9% 26.8% 36.1%

15.4% 6.4% 14.3% 36.1%18.3 -5.0 -13.23.8 -1.1 -1.95.5 -1.5 -3.416 13 70 99

23.4 22.7 52.8 99.016.2% 13.1% 70.7% 100.0%

25.4% 21.3% 49.3% 37.2%

6.0% 4.9% 26.3% 37.2%-7.4 -9.7 17.2-1.5 -2.0 2.4-2.2 -2.9 4.4

0 0 1 1.2 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.2 -.2 .5-.5 -.5 .6-.6 -.5 .963 61 142 266

63.0 61.0 142.0 266.023.7% 22.9% 53.4% 100.0%

100.0% 100.0% 100.0% 100.0%

23.7% 22.9% 53.4% 100.0%

CountExpected Count% within Country% within I needhelp with shopping% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with shopping% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with shopping% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with shopping% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with shopping% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with shopping% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI need help with shopping

Total

Chi-Square Tests

59.637a 8 .00065.734 8 .000

.578 1 .447

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .23.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.131 .053 2.336 .019

.180 .051 3.261 .001

.065 .078 .801 .423

.083 .022 .000c

.110 .027 .000c

.108 .021 4.973 .000d

.096 .019 4.973 .000d

.122 .024 4.973 .000d

-.144 .049 -2.949 .003-.155 .053 -2.949 .003

-.135 .046 -2.949 .003

.299

.361

SymmetricCountry DependentI need help withshopping DependentCountry DependentI need help withshopping DependentSymmetricCountry DependentI need help withshopping DependentSymmetricCountry DependentI need help withshopping DependentCountry DependentI need help withshopping Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.473 .000

.335 .000

.428 .000-.145 .049 -2.949 .003-.141 .048 -2.949 .003-.212 .071 -2.949 .003

-.172 .057 -2.830 .005c

-.047 .053 -.760 .448c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I need help with sho

Yes

No

Country * I need help with cleaning

Crosstab

7 10 10 276.5 4.5 16.0 27.0

25.9% 37.0% 37.0% 100.0%

10.9% 22.7% 6.3% 10.2%

2.6% 3.8% 3.8% 10.2%.5 5.5 -6.0.2 2.6 -1.5.2 3.0 -2.50 10 33 43

10.3 7.1 25.5 43.0.0% 23.3% 76.7% 100.0%

.0% 22.7% 20.9% 16.2%

.0% 3.8% 12.4% 16.2%-10.3 2.9 7.5-3.2 1.1 1.5-4.0 1.3 2.5

44 13 39 9623.1 15.9 57.0 96.0

45.8% 13.5% 40.6% 100.0%

68.8% 29.5% 24.7% 36.1%

16.5% 4.9% 14.7% 36.1%20.9 -2.9 -18.04.3 -.7 -2.46.2 -1.0 -4.713 10 76 99

23.8 16.4 58.8 99.013.1% 10.1% 76.8% 100.0%

20.3% 22.7% 48.1% 37.2%

4.9% 3.8% 28.6% 37.2%-10.8 -6.4 17.2-2.2 -1.6 2.2-3.2 -2.2 4.4

0 1 0 1.2 .2 .6 1.0

.0% 100.0% .0% 100.0%

.0% 2.3% .0% .4%

.0% .4% .0% .4%-.2 .8 -.6-.5 2.1 -.8-.6 2.3 -1.264 44 158 266

64.0 44.0 158.0 266.024.1% 16.5% 59.4% 100.0%

100.0% 100.0% 100.0% 100.0%

24.1% 16.5% 59.4% 100.0%

CountExpected Count% within Country% within I needhelp with cleaning% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with cleaning% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with cleaning% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with cleaning% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with cleaning% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with cleaning% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI need help with cleaning

Total

Chi-Square Tests

65.469a 8 .00070.302 8 .000

1.005 1 .316

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .17.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.145 .056 2.453 .014

.204 .048 3.909 .000

.056 .092 .589 .556

.091 .023 .000c

.135 .031 .000c

.118 .023 5.110 .000d

.103 .020 5.110 .000d

.139 .027 5.110 .000d

-.127 .049 -2.595 .009-.142 .055 -2.595 .009

-.115 .045 -2.595 .009

.205

.421

SymmetricCountry DependentI need help withcleaning DependentCountry DependentI need help withcleaning DependentSymmetricCountry DependentI need help withcleaning DependentSymmetricCountry DependentI need help withcleaning DependentCountry DependentI need help withcleaning Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.496 .000

.351 .000

.444 .000-.128 .050 -2.595 .009-.120 .046 -2.595 .009-.193 .074 -2.595 .009

-.149 .057 -2.453 .015c

-.062 .053 -1.003 .317c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I need help with cle

Yes

No

Country * I need help with cleaning my house

Crosstab

6 13 8 276.1 6.9 14.0 27.0

22.2% 48.1% 29.6% 100.0%

10.0% 19.1% 5.8% 10.2%

2.3% 4.9% 3.0% 10.2%-.1 6.1 -6.0.0 2.3 -1.6.0 2.8 -2.40 14 29 43

9.7 11.0 22.3 43.0.0% 32.6% 67.4% 100.0%

.0% 20.6% 21.0% 16.2%

.0% 5.3% 10.9% 16.2%-9.7 3.0 6.7-3.1 .9 1.4-3.9 1.1 2.2

40 16 40 9621.7 24.5 49.8 96.0

41.7% 16.7% 41.7% 100.0%

66.7% 23.5% 29.0% 36.1%

15.0% 6.0% 15.0% 36.1%18.3 -8.5 -9.83.9 -1.7 -1.45.6 -2.5 -2.514 25 60 99

22.3 25.3 51.4 99.014.1% 25.3% 60.6% 100.0%

23.3% 36.8% 43.5% 37.2%

5.3% 9.4% 22.6% 37.2%-8.3 -.3 8.6-1.8 -.1 1.2-2.5 -.1 2.2

0 0 1 1.2 .3 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.2 -.3 .5-.5 -.5 .7-.5 -.6 1.060 68 138 266

60.0 68.0 138.0 266.022.6% 25.6% 51.9% 100.0%

100.0% 100.0% 100.0% 100.0%

22.6% 25.6% 51.9% 100.0%

CountExpected Count% within Country% within I need helpwith cleaning my house% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith cleaning my house% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith cleaning my house% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith cleaning my house% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith cleaning my house% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith cleaning my house% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI need help with cleaning my house

Total

Chi-Square Tests

46.432a 8 .00053.457 8 .000

.210 1 .647

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .23.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.105 .050 2.038 .042

.156 .040 3.624 .000

.039 .077 .498 .619

.064 .019 .000c

.081 .022 .000c

.087 .018 4.674 .000d

.078 .016 4.674 .000d

.098 .021 4.674 .000d

-.078 .049 -1.604 .109-.083 .052 -1.604 .109

-.073 .046 -1.604 .109

.146

.361

SymmetricCountry DependentI need help with cleaningmy house DependentCountry DependentI need help with cleaningmy house DependentSymmetricCountry DependentI need help with cleaningmy house DependentSymmetricCountry DependentI need help with cleaningmy house DependentCountry DependentI need help with cleaningmy house Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.418 .000

.295 .000

.386 .000-.078 .049 -1.604 .109-.076 .048 -1.604 .109-.116 .072 -1.604 .109

-.089 .057 -1.460 .146c

-.028 .053 -.458 .647c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

I need help with cle

Yes

No

Country * I need help with personal care (bathroom, toilet,...)

Crosstab

7 8 12 276.8 2.6 17.6 27.0

25.9% 29.6% 44.4% 100.0%

10.4% 30.8% 6.9% 10.2%

2.6% 3.0% 4.5% 10.2%.2 5.4 -5.6.1 3.3 -1.3.1 3.7 -2.40 6 37 43

10.8 4.2 28.0 43.0.0% 14.0% 86.0% 100.0%

.0% 23.1% 21.4% 16.2%

.0% 2.3% 13.9% 16.2%-10.8 1.8 9.0-3.3 .9 1.7-4.2 1.0 3.2

46 8 42 9624.2 9.4 62.4 96.0

47.9% 8.3% 43.8% 100.0%

68.7% 30.8% 24.3% 36.1%

17.3% 3.0% 15.8% 36.1%21.8 -1.4 -20.44.4 -.5 -2.66.4 -.6 -5.514 4 81 99

24.9 9.7 64.4 99.014.1% 4.0% 81.8% 100.0%

20.9% 15.4% 46.8% 37.2%

5.3% 1.5% 30.5% 37.2%-10.9 -5.7 16.6-2.2 -1.8 2.1-3.2 -2.4 4.4

0 0 1 1.3 .1 .7 1.0

.0% .0% 100.0% 100.0%

.0% .0% .6% .4%

.0% .0% .4% .4%-.3 -.1 .3-.5 -.3 .4-.6 -.3 .767 26 173 266

67.0 26.0 173.0 266.025.2% 9.8% 65.0% 100.0%

100.0% 100.0% 100.0% 100.0%

25.2% 9.8% 65.0% 100.0%

CountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith personal care(bathroom, toilet,...)% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I need help with personal care(bathroom, toilet,...)

Total

Chi-Square Tests

66.706a 8 .00072.120 8 .000

.679 1 .410

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (33.3%) have expected count less than 5. The minimumexpected count is .10.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.154 .057 2.550 .011

.216 .045 4.394 .000

.043 .099 .427 .670

.097 .024 .000c

.155 .035 .000c

.127 .024 5.182 .000d

.106 .020 5.182 .000d

.159 .030 5.182 .000d

-.123 .050 -2.493 .013-.146 .059 -2.493 .013

-.106 .043 -2.493 .013

.245

.432

SymmetricCountry DependentI need help with personalcare (bathroom, toilet,...)DependentCountry DependentI need help with personalcare (bathroom, toilet,...)DependentSymmetricCountry DependentI need help with personalcare (bathroom, toilet,...)DependentSymmetricCountry DependentI need help with personalcare (bathroom, toilet,...)DependentCountry DependentI need help with personalcare (bathroom, toilet,...)Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.501 .000

.354 .000

.448 .000-.125 .050 -2.493 .013-.111 .044 -2.493 .013-.197 .078 -2.493 .013

-.143 .057 -2.351 .019c

-.051 .053 -.823 .411c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

I need help with per

Yes

No

Country * I need help with nursing care

Crosstab

8 5 14 276.9 3.3 16.7 27.0

29.6% 18.5% 51.9% 100.0%

11.8% 15.2% 8.5% 10.2%

3.0% 1.9% 5.3% 10.2%1.1 1.7 -2.7.4 .9 -.7.5 1.0 -1.10 4 39 43

11.0 5.3 26.7 43.0.0% 9.3% 90.7% 100.0%

.0% 12.1% 23.6% 16.2%

.0% 1.5% 14.7% 16.2%-11.0 -1.3 12.3-3.3 -.6 2.4-4.2 -.7 4.2

46 12 38 9624.5 11.9 59.5 96.0

47.9% 12.5% 39.6% 100.0%

67.6% 36.4% 23.0% 36.1%

17.3% 4.5% 14.3% 36.1%21.5 .1 -21.54.3 .0 -2.86.3 .0 -5.714 12 73 99

25.3 12.3 61.4 99.014.1% 12.1% 73.7% 100.0%

20.6% 36.4% 44.2% 37.2%

5.3% 4.5% 27.4% 37.2%-11.3 -.3 11.6-2.2 -.1 1.5-3.3 -.1 3.0

0 0 1 1.3 .1 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .6% .4%

.0% .0% .4% .4%-.3 -.1 .4-.5 -.4 .5-.6 -.4 .868 33 165 266

68.0 33.0 165.0 266.025.6% 12.4% 62.0% 100.0%

100.0% 100.0% 100.0% 100.0%

25.6% 12.4% 62.0% 100.0%

CountExpected Count% within Country% within I need helpwith nursing care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith nursing care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith nursing care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith nursing care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith nursing care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith nursing care% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI need help with nursing care

Total

Chi-Square Tests

52.883a 8 .00061.583 8 .000

.288 1 .592

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .12.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.149 .054 2.638 .008

.192 .042 4.270 .000

.079 .087 .874 .382

.082 .022 .000c

.136 .032 .000c

.106 .021 5.064 .000d

.090 .018 5.064 .000d

.128 .025 5.064 .000d

-.060 .051 -1.175 .240-.069 .059 -1.175 .240

-.053 .045 -1.175 .240

.045

.438

SymmetricCountry DependentI need help with nursingcare DependentCountry DependentI need help with nursingcare DependentSymmetricCountry DependentI need help with nursingcare DependentSymmetricCountry DependentI need help with nursingcare DependentCountry DependentI need help with nursingcare Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.446 .000

.315 .000

.407 .000-.060 .051 -1.175 .240-.055 .047 -1.175 .240-.095 .080 -1.175 .240

-.067 .058 -1.092 .276c

-.033 .055 -.536 .593c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I need help with nur

Yes

No

Country * I need help to arrange my personal affairs (bank, servises)

Crosstab

7 8 12 277.1 5.7 14.2 27.0

25.9% 29.6% 44.4% 100.0%

10.0% 14.3% 8.6% 10.2%

2.6% 3.0% 4.5% 10.2%-.1 2.3 -2.2.0 1.0 -.6.0 1.2 -.90 23 20 43

11.3 9.1 22.6 43.0.0% 53.5% 46.5% 100.0%

.0% 41.1% 14.3% 16.2%

.0% 8.6% 7.5% 16.2%-11.3 13.9 -2.6-3.4 4.6 -.6-4.3 5.7 -.9

45 15 36 9625.3 20.2 50.5 96.0

46.9% 15.6% 37.5% 100.0%

64.3% 26.8% 25.7% 36.1%

16.9% 5.6% 13.5% 36.1%19.7 -5.2 -14.53.9 -1.2 -2.05.7 -1.6 -3.718 10 71 99

26.1 20.8 52.1 99.018.2% 10.1% 71.7% 100.0%

25.7% 17.9% 50.7% 37.2%

6.8% 3.8% 26.7% 37.2%-8.1 -10.8 18.9-1.6 -2.4 2.6-2.3 -3.4 4.8

0 0 1 1.3 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .5-.5 -.5 .7-.6 -.5 1.070 56 140 266

70.0 56.0 140.0 266.026.3% 21.1% 52.6% 100.0%

100.0% 100.0% 100.0% 100.0%

26.3% 21.1% 52.6% 100.0%

CountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help toarrange my personalaffairs (bank, servises)% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I need help to arrange my personalaffairs (bank, servises)

Total

Chi-Square Tests

71.219a 8 .00074.978 8 .000

.453 1 .501

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .21.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.177 .060 2.796 .005

.240 .051 4.217 .000

.095 .084 1.080 .280

.101 .025 .000c

.126 .029 .000c

.123 .023 5.207 .000d

.110 .021 5.207 .000d

.139 .026 5.207 .000d

-.139 .051 -2.768 .006-.149 .055 -2.768 .006

-.131 .048 -2.768 .006

.289

.365

SymmetricCountry DependentI need help to arrange mypersonal affairs (bank,servises) DependentCountry DependentI need help to arrange mypersonal affairs (bank,servises) DependentSymmetricCountry DependentI need help to arrange mypersonal affairs (bank,servises) DependentSymmetricCountry DependentI need help to arrange mypersonal affairs (bank,servises) DependentCountry DependentI need help to arrange mypersonal affairs (bank,servises) Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.517 .000

.366 .000

.460 .000-.140 .051 -2.768 .006-.136 .049 -2.768 .006-.203 .073 -2.768 .006

-.170 .059 -2.805 .005c

-.041 .055 -.672 .502c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I need help to arran

Yes

No

Country * I need help with transport to doctor or to hospital

Crosstab

7 12 8 276.2 6.3 14.5 27.0

25.9% 44.4% 29.6% 100.0%

11.5% 19.4% 5.6% 10.2%

2.6% 4.5% 3.0% 10.2%.8 5.7 -6.5.3 2.3 -1.7.4 2.7 -2.70 10 33 43

9.9 10.0 23.1 43.0.0% 23.3% 76.7% 100.0%

.0% 16.1% 23.1% 16.2%

.0% 3.8% 12.4% 16.2%-9.9 .0 9.9-3.1 .0 2.1-3.9 .0 3.3

38 26 32 9622.0 22.4 51.6 96.0

39.6% 27.1% 33.3% 100.0%

62.3% 41.9% 22.4% 36.1%

14.3% 9.8% 12.0% 36.1%16.0 3.6 -19.63.4 .8 -2.74.9 1.1 -5.016 13 70 99

22.7 23.1 53.2 99.016.2% 13.1% 70.7% 100.0%

26.2% 21.0% 49.0% 37.2%

6.0% 4.9% 26.3% 37.2%-6.7 -10.1 16.8-1.4 -2.1 2.3-2.0 -3.0 4.3

0 1 0 1.2 .2 .5 1.0

.0% 100.0% .0% 100.0%

.0% 1.6% .0% .4%

.0% .4% .0% .4%-.2 .8 -.5-.5 1.6 -.7-.5 1.8 -1.161 62 143 266

61.0 62.0 143.0 266.022.9% 23.3% 53.8% 100.0%

100.0% 100.0% 100.0% 100.0%

22.9% 23.3% 53.8% 100.0%

CountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need helpwith transport todoctor or to hospital% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I need help with transport to doctoror to hospital

Total

Chi-Square Tests

56.893a 8 .00064.987 8 .000

.370 1 .543

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .23.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.159 .051 2.897 .004

.210 .051 3.723 .000

.089 .074 1.156 .248

.079 .021 .000c

.121 .028 .000c

.106 .021 5.075 .000d

.095 .018 5.075 .000d

.121 .024 5.075 .000d

-.104 .052 -2.029 .042-.112 .056 -2.029 .042

-.097 .048 -2.029 .042

.187

.383

SymmetricCountry DependentI need help withtransport to doctor orto hospital DependentCountry DependentI need help withtransport to doctor orto hospital DependentSymmetricCountry DependentI need help withtransport to doctor orto hospital DependentSymmetricCountry DependentI need help withtransport to doctor orto hospital DependentCountry DependentI need help withtransport to doctor orto hospital Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.462 .000

.327 .000

.420 .000-.104 .052 -2.029 .042-.102 .050 -2.029 .042-.154 .076 -2.029 .042

-.122 .059 -2.000 .047c

-.037 .055 -.608 .544c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I need help with tra

Yes

No

Country * I need help with lonliness (I need company)

Crosstab

7 7 13 276.5 6.3 14.2 27.0

25.9% 25.9% 48.1% 100.0%

10.9% 11.3% 9.3% 10.2%

2.6% 2.6% 4.9% 10.2%.5 .7 -1.2.2 .3 -.3.2 .3 -.50 20 23 43

10.3 10.0 22.6 43.0.0% 46.5% 53.5% 100.0%

.0% 32.3% 16.4% 16.2%

.0% 7.5% 8.6% 16.2%-10.3 10.0 .4-3.2 3.2 .1-4.0 3.9 .1

38 18 40 9623.1 22.4 50.5 96.0

39.6% 18.8% 41.7% 100.0%

59.4% 29.0% 28.6% 36.1%

14.3% 6.8% 15.0% 36.1%14.9 -4.4 -10.53.1 -.9 -1.54.5 -1.3 -2.719 17 63 99

23.8 23.1 52.1 99.019.2% 17.2% 63.6% 100.0%

29.7% 27.4% 45.0% 37.2%

7.1% 6.4% 23.7% 37.2%-4.8 -6.1 10.9-1.0 -1.3 1.5-1.4 -1.8 2.8

0 0 1 1.2 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.2 -.2 .5-.5 -.5 .7-.6 -.6 1.064 62 140 266

64.0 62.0 140.0 266.024.1% 23.3% 52.6% 100.0%

100.0% 100.0% 100.0% 100.0%

24.1% 23.3% 52.6% 100.0%

CountExpected Count% within Country% within I needhelp with lonliness(I need company)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with lonliness(I need company)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with lonliness(I need company)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with lonliness(I need company)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with lonliness(I need company)% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I needhelp with lonliness(I need company)% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I need help with lonliness (I needcompany)

Total

Chi-Square Tests

38.922a 8 .00046.141 8 .000

.005 1 .945

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .23.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.075 .031 2.291 .022

.132 .054 2.291 .022

.000 .000 .c

.c

.052 .018 .000d

.066 .019 .000d

.075 .016 4.571 .000e

.068 .015 4.571 .000e

.085 .018 4.571 .000e

-.070 .051 -1.368 .171-.075 .055 -1.368 .171

-.066 .048 -1.368 .171

.164

.299

SymmetricCountry DependentI need help withlonliness (I needcompany) DependentCountry DependentI need help withlonliness (I needcompany) DependentSymmetricCountry DependentI need help withlonliness (I needcompany) DependentSymmetricCountry DependentI need help withlonliness (I needcompany) DependentCountry DependentI need help withlonliness (I needcompany) Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Symmetric Measures

.383 .000

.270 .000

.357 .000-.070 .051 -1.368 .171-.069 .050 -1.368 .171-.105 .076 -1.368 .171

-.085 .059 -1.381 .168c

-.004 .057 -.068 .946c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

I need help with lon

Yes

No

Country * I need help to take care about my pet

Crosstab

8 4 15 278.0 1.2 17.8 27.0

29.6% 14.8% 55.6% 100.0%

10.1% 33.3% 8.6% 10.2%

3.0% 1.5% 5.6% 10.2%.0 2.8 -2.8.0 2.5 -.7.0 2.7 -1.20 2 41 43

12.8 1.9 28.3 43.0.0% 4.7% 95.3% 100.0%

.0% 16.7% 23.4% 16.2%

.0% .8% 15.4% 16.2%-12.8 .1 12.7-3.6 .0 2.4-4.7 .0 4.5

51 4 41 9628.5 4.3 63.2 96.0

53.1% 4.2% 42.7% 100.0%

64.6% 33.3% 23.4% 36.1%

19.2% 1.5% 15.4% 36.1%22.5 -.3 -22.24.2 -.2 -2.86.3 -.2 -6.020 2 77 99

29.4 4.5 65.1 99.020.2% 2.0% 77.8% 100.0%

25.3% 16.7% 44.0% 37.2%

7.5% .8% 28.9% 37.2%-9.4 -2.5 11.9-1.7 -1.2 1.5-2.6 -1.5 3.2

0 0 1 1.3 .0 .7 1.0

.0% .0% 100.0% 100.0%

.0% .0% .6% .4%

.0% .0% .4% .4%-.3 .0 .3-.5 -.2 .4-.7 -.2 .779 12 175 266

79.0 12.0 175.0 266.029.7% 4.5% 65.8% 100.0%

100.0% 100.0% 100.0% 100.0%

29.7% 4.5% 65.8% 100.0%

CountExpected Count% within Country% within I need help totake care about my pet% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help totake care about my pet% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help totake care about my pet% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help totake care about my pet% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help totake care about my pet% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I need help totake care about my pet% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I need help to take care about mypet

Total

Chi-Square Tests

57.856a 8 .00066.193 8 .000

.011 1 .915

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

7 cells (46.7%) have expected count less than 5. The minimumexpected count is .05.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.167 .059 2.646 .008

.198 .047 3.865 .000

.110 .099 1.045 .296

.083 .022 .000c

.166 .037 .000c

.121 .022 5.291 .000d

.097 .018 5.291 .000d

.160 .030 5.291 .000d

-.043 .052 -.831 .406-.053 .063 -.831 .406

-.036 .044 -.831 .406

.152

.431

SymmetricCountry DependentI need help to take careabout my pet DependentCountry DependentI need help to take careabout my pet DependentSymmetricCountry DependentI need help to take careabout my pet DependentSymmetricCountry DependentI need help to take careabout my pet DependentCountry DependentI need help to take careabout my pet Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.466 .000

.330 .000

.423 .000-.044 .052 -.831 .406-.038 .045 -.831 .406-.072 .086 -.831 .406

-.049 .058 -.799 .425c

.007 .055 .106 .916c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

I need help to take

Yes

No

Country * I feel lonely

Crosstab

11 2 5 2 6 1 276.2 8.0 4.9 2.1 3.6 2.2 27.0

40.7% 7.4% 18.5% 7.4% 22.2% 3.7% 100.0%18.0% 2.5% 10.4% 9.5% 17.1% 4.5% 10.2%4.1% .8% 1.9% .8% 2.3% .4% 10.2%

4.8 -6.0 .1 -.1 2.4 -1.21.9 -2.1 .1 -.1 1.3 -.82.3 -2.7 .1 -.1 1.5 -.9

0 22 7 3 4 7 439.9 12.8 7.8 3.4 5.7 3.6 43.0

.0% 51.2% 16.3% 7.0% 9.3% 16.3% 100.0%

.0% 27.8% 14.6% 14.3% 11.4% 31.8% 16.2%

.0% 8.3% 2.6% 1.1% 1.5% 2.6% 16.2%-9.9 9.2 -.8 -.4 -1.7 3.4-3.1 2.6 -.3 -.2 -.7 1.8-3.9 3.4 -.3 -.2 -.8 2.1

41 11 18 11 14 1 9622.0 28.5 17.3 7.6 12.6 7.9 96.0

42.7% 11.5% 18.8% 11.5% 14.6% 1.0% 100.0%67.2% 13.9% 37.5% 52.4% 40.0% 4.5% 36.1%15.4% 4.1% 6.8% 4.1% 5.3% .4% 36.1%

19.0 -17.5 .7 3.4 1.4 -6.94.0 -3.3 .2 1.2 .4 -2.55.8 -4.9 .2 1.6 .5 -3.2

8 44 18 5 11 13 9922.7 29.4 17.9 7.8 13.0 8.2 99.0

8.1% 44.4% 18.2% 5.1% 11.1% 13.1% 100.0%13.1% 55.7% 37.5% 23.8% 31.4% 59.1% 37.2%3.0% 16.5% 6.8% 1.9% 4.1% 4.9% 37.2%-14.7 14.6 .1 -2.8 -2.0 4.8-3.1 2.7 .0 -1.0 -.6 1.7-4.4 4.1 .0 -1.3 -.8 2.2

1 0 0 0 0 0 1.2 .3 .2 .1 .1 .1 1.0

100.0% .0% .0% .0% .0% .0% 100.0%1.6% .0% .0% .0% .0% .0% .4%.4% .0% .0% .0% .0% .0% .4%

.8 -.3 -.2 -.1 -.1 -.11.6 -.5 -.4 -.3 -.4 -.31.8 -.7 -.5 -.3 -.4 -.361 79 48 21 35 22 266

61.0 79.0 48.0 21.0 35.0 22.0 266.022.9% 29.7% 18.0% 7.9% 13.2% 8.3% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%22.9% 29.7% 18.0% 7.9% 13.2% 8.3% 100.0%

CountExpected Count% within Country% within I feel lonely% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel lonely% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel lonely% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel lonely% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel lonely% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel lonely% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I feel lonely

Total

Chi-Square Tests

90.302a 20 .000104.413 20 .000

.841 1 .359

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

12 cells (40.0%) have expected count less than 5. The minimumexpected count is .08.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.232 .038 5.622 .000

.251 .049 4.600 .000

.214 .039 5.165 .000

.134 .023 .000c

.095 .017 .000c

.132 .020 6.536 .000d

.153 .023 6.536 .000d

.117 .018 6.536 .000d

-.037 .050 -.750 .453-.035 .047 -.750 .453-.040 .054 -.750 .453.178.316

SymmetricCountry DependentI feel lonely DependentCountry DependentI feel lonely DependentSymmetricCountry DependentI feel lonely DependentSymmetricCountry DependentI feel lonely DependentCountry DependentI feel lonely Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.583 .000

.291 .000

.503 .000-.038 .050 -.750 .453-.035 .046 -.750 .453-.049 .065 -.750 .453

-.045 .061 -.738 .461c

-.056 .062 -.917 .360c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

I feel lonely

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * Gender

Crosstab

8 19 278.4 18.6 27.0

29.6% 70.4% 100.0%9.6% 10.4% 10.2%3.0% 7.1% 10.2%

-.4 .4-.1 .1-.2 .219 24 43

13.4 29.6 43.044.2% 55.8% 100.0%22.9% 13.1% 16.2%7.1% 9.0% 16.2%

5.6 -5.61.5 -1.02.0 -2.027 69 96

30.0 66.0 96.028.1% 71.9% 100.0%32.5% 37.7% 36.1%10.2% 25.9% 36.1%

-3.0 3.0-.5 .4-.8 .828 71 99

30.9 68.1 99.028.3% 71.7% 100.0%33.7% 38.8% 37.2%10.5% 26.7% 37.2%

-2.9 2.9-.5 .4-.8 .8

1 0 1.3 .7 1.0

100.0% .0% 100.0%1.2% .0% .4%.4% .0% .4%

.7 -.71.2 -.81.5 -1.583 183 266

83.0 183.0 266.031.2% 68.8% 100.0%

100.0% 100.0% 100.0%31.2% 68.8% 100.0%

CountExpected Count% within Country% within Gender% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Gender% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Gender% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Gender% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Gender% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Gender% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Male FemaleGender

Total

Chi-Square Tests

6.429a 4 .1696.374 4 .173

.713 1 .398

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

2 cells (20.0%) have expected count less than 5. The minimumexpected count is .31.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.004 .004 1.002 .316

.000 .000 .c .c

.012 .012 1.002 .316

.005 .005 .296d

.024 .016 .171d

.013 .009 1.357 .173e

.009 .007 1.357 .173e

.019 .014 1.357 .173e

-.053 .056 -.939 .348-.069 .073 -.939 .348-.043 .045 -.939 .348.052.155

SymmetricCountry DependentGender DependentCountry DependentGender DependentSymmetricCountry DependentGender DependentSymmetricCountry DependentGender DependentCountry DependentGender Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Symmetric Measures

.155 .169

.155 .169

.154 .169-.054 .058 -.939 .348-.059 .063 -.939 .348-.098 .103 -.939 .348

-.058 .062 -.952 .342c

-.052 .062 -.844 .399c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

Gender

Male

Female

Country * I am satisfied with my life

Crosstab

6 0 2 1 14 4 273.8 1.5 1.6 3.3 9.3 7.4 27.0

22.2% .0% 7.4% 3.7% 51.9% 14.8% 100.0%

16.2% .0% 12.5% 3.0% 15.2% 5.5% 10.2%

2.3% .0% .8% .4% 5.3% 1.5% 10.2%2.2 -1.5 .4 -2.3 4.7 -3.41.2 -1.2 .3 -1.3 1.5 -1.31.3 -1.3 .3 -1.4 2.0 -1.6

0 2 5 8 11 17 436.0 2.4 2.6 5.3 14.9 11.8 43.0

.0% 4.7% 11.6% 18.6% 25.6% 39.5% 100.0%

.0% 13.3% 31.3% 24.2% 12.0% 23.3% 16.2%

.0% .8% 1.9% 3.0% 4.1% 6.4% 16.2%-6.0 -.4 2.4 2.7 -3.9 5.2-2.4 -.3 1.5 1.2 -1.0 1.5-2.9 -.3 1.7 1.3 -1.4 1.9

28 4 8 12 33 11 9613.4 5.4 5.8 11.9 33.2 26.3 96.0

29.2% 4.2% 8.3% 12.5% 34.4% 11.5% 100.0%

75.7% 26.7% 50.0% 36.4% 35.9% 15.1% 36.1%

10.5% 1.5% 3.0% 4.5% 12.4% 4.1% 36.1%14.6 -1.4 2.2 .1 -.2 -15.34.0 -.6 .9 .0 .0 -3.05.4 -.8 1.2 .0 -.1 -4.4

3 8 1 12 34 41 9913.8 5.6 6.0 12.3 34.2 27.2 99.0

3.0% 8.1% 1.0% 12.1% 34.3% 41.4% 100.0%

8.1% 53.3% 6.3% 36.4% 37.0% 56.2% 37.2%

1.1% 3.0% .4% 4.5% 12.8% 15.4% 37.2%-10.8 2.4 -5.0 -.3 -.2 13.8-2.9 1.0 -2.0 -.1 .0 2.7-3.9 1.3 -2.6 -.1 -.1 3.9

0 1 0 0 0 0 1.1 .1 .1 .1 .3 .3 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 6.7% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.1 .9 -.1 -.1 -.3 -.3-.4 4.0 -.2 -.4 -.6 -.5-.4 4.1 -.3 -.4 -.7 -.637 15 16 33 92 73 266

37.0 15.0 16.0 33.0 92.0 73.0 266.013.9% 5.6% 6.0% 12.4% 34.6% 27.4% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

13.9% 5.6% 6.0% 12.4% 34.6% 27.4% 100.0%

CountExpected Count% within Country% within I amsatisfied with my life% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amsatisfied with my life% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amsatisfied with my life% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amsatisfied with my life% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amsatisfied with my life% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I amsatisfied with my life% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I am satisfied with my life

Total

Chi-Square Tests

85.042a 20 .00084.846 20 .000

3.076 1 .079

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

12 cells (40.0%) have expected count less than 5. The minimumexpected count is .06.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.135 .032 3.944 .000

.192 .034 5.322 .000

.080 .056 1.378 .168

.109 .021 .000c

.065 .014 .000c

.111 .019 5.565 .000d

.124 .022 5.565 .000d

.101 .018 5.565 .000d

-.129 .050 -2.620 .009-.123 .047 -2.620 .009

-.136 .053 -2.620 .009

.237

.394

SymmetricCountry DependentI am satisfied withmy life DependentCountry DependentI am satisfied withmy life DependentSymmetricCountry DependentI am satisfied withmy life DependentSymmetricCountry DependentI am satisfied withmy life DependentCountry DependentI am satisfied withmy life Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.565 .000

.283 .000

.492 .000-.129 .050 -2.620 .009-.118 .045 -2.620 .009-.173 .066 -2.620 .009

-.156 .060 -2.569 .011c

-.108 .056 -1.761 .079c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

I am satisfied with

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * I feel that my family cares about me

Crosstab

9 0 0 1 13 4 273.8 1.0 .5 .9 9.0 11.8 27.0

33.3% .0% .0% 3.7% 48.1% 14.8% 100.0%

24.3% .0% .0% 11.1% 14.6% 3.4% 10.2%

3.4% .0% .0% .4% 4.9% 1.5% 10.2%5.2 -1.0 -.5 .1 4.0 -7.82.7 -1.0 -.7 .1 1.3 -2.33.1 -1.1 -.8 .1 1.7 -3.2

0 3 2 4 18 16 436.0 1.6 .8 1.5 14.4 18.8 43.0

.0% 7.0% 4.7% 9.3% 41.9% 37.2% 100.0%

.0% 30.0% 40.0% 44.4% 20.2% 13.8% 16.2%

.0% 1.1% .8% 1.5% 6.8% 6.0% 16.2%-6.0 1.4 1.2 2.5 3.6 -2.8-2.4 1.1 1.3 2.1 1.0 -.6-2.9 1.2 1.5 2.3 1.3 -.9

25 1 2 3 38 27 9613.4 3.6 1.8 3.2 32.1 41.9 96.0

26.0% 1.0% 2.1% 3.1% 39.6% 28.1% 100.0%

67.6% 10.0% 40.0% 33.3% 42.7% 23.3% 36.1%

9.4% .4% .8% 1.1% 14.3% 10.2% 36.1%11.6 -2.6 .2 -.2 5.9 -14.93.2 -1.4 .1 -.1 1.0 -2.34.3 -1.8 .2 -.2 1.6 -3.8

3 5 1 1 20 69 9913.8 3.7 1.9 3.3 33.1 43.2 99.0

3.0% 5.1% 1.0% 1.0% 20.2% 69.7% 100.0%

8.1% 50.0% 20.0% 11.1% 22.5% 59.5% 37.2%

1.1% 1.9% .4% .4% 7.5% 25.9% 37.2%-10.8 1.3 -.9 -2.3 -13.1 25.8-2.9 .7 -.6 -1.3 -2.3 3.9-3.9 .9 -.8 -1.6 -3.5 6.6

0 1 0 0 0 0 1.1 .0 .0 .0 .3 .4 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 10.0% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.1 1.0 .0 .0 -.3 -.4-.4 5.0 -.1 -.2 -.6 -.7-.4 5.1 -.1 -.2 -.7 -.937 10 5 9 89 116 266

37.0 10.0 5.0 9.0 89.0 116.0 266.013.9% 3.8% 1.9% 3.4% 33.5% 43.6% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

13.9% 3.8% 1.9% 3.4% 33.5% 43.6% 100.0%

CountExpected Count% within Country% within I feel that myfamily cares about me% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel that myfamily cares about me% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel that myfamily cares about me% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel that myfamily cares about me% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel that myfamily cares about me% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I feel that myfamily cares about me% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

I feel that my family cares about me

Total

Chi-Square Tests

106.013a 20 .00094.201 20 .000

12.375 1 .000

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

19 cells (63.3%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.211 .047 4.077 .000

.263 .050 4.725 .000

.153 .066 2.145 .032

.122 .025 .000c

.114 .025 .000c

.136 .024 5.583 .000d

.138 .024 5.583 .000d

.135 .023 5.583 .000d

-.289 .049 -6.017 .000-.293 .050 -6.017 .000

-.285 .048 -6.017 .000

.369

.377

SymmetricCountry DependentI feel that my family caresabout me DependentCountry DependentI feel that my family caresabout me DependentSymmetricCountry DependentI feel that my family caresabout me DependentSymmetricCountry DependentI feel that my family caresabout me DependentCountry DependentI feel that my family caresabout me Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.631 .000

.316 .000

.534 .000-.289 .049 -6.017 .000-.247 .041 -6.017 .000-.399 .065 -6.017 .000

-.337 .056 -5.817 .000c

-.216 .058 -3.596 .000c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I feel that my famil

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * Is there a Voluntary Organisation for support for Elder people in your city?

Crosstab

4 20 3 274.8 9.7 12.5 27.0

14.8% 74.1% 11.1% 100.0%

8.5% 20.8% 2.4% 10.2%

1.5% 7.5% 1.1% 10.2%-.8 10.3 -9.5-.4 3.3 -2.7-.4 4.3 -3.9

0 0 43 437.6 15.5 19.9 43.0

.0% .0% 100.0% 100.0%

.0% .0% 35.0% 16.2%

.0% .0% 16.2% 16.2%-7.6 -15.5 23.1-2.8 -3.9 5.2-3.3 -5.4 7.7

32 32 32 9617.0 34.6 44.4 96.0

33.3% 33.3% 33.3% 100.0%

68.1% 33.3% 26.0% 36.1%

12.0% 12.0% 12.0% 36.1%15.0 -2.6 -12.43.7 -.4 -1.95.0 -.7 -3.211 44 44 99

17.5 35.7 45.8 99.011.1% 44.4% 44.4% 100.0%

23.4% 45.8% 35.8% 37.2%

4.1% 16.5% 16.5% 37.2%-6.5 8.3 -1.8-1.6 1.4 -.3-2.2 2.2 -.5

0 0 1 1.2 .4 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .8% .4%

.0% .0% .4% .4%-.2 -.4 .5-.4 -.6 .8-.5 -.8 1.147 96 123 266

47.0 96.0 123.0 266.017.7% 36.1% 46.2% 100.0%

100.0% 100.0% 100.0% 100.0%

17.7% 36.1% 46.2% 100.0%

CountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Is there aVoluntary Organisationfor support for Elderpeople in your city?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Is there a Voluntary Organisation forsupport for Elder people in your city?

Total

Chi-Square Tests

90.664a 8 .000105.894 8 .000

.264 1 .608

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .18.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.123 .051 2.285 .022

.126 .037 3.266 .001

.119 .087 1.289 .197

.096 .021 .000c

.194 .021 .000c

.172 .023 7.268 .000d

.155 .020 7.268 .000d

.193 .026 7.268 .000d

.039 .050 .789 .430

.042 .053 .789 .430

.037 .047 .789 .430

.038

.406

SymmetricCountry DependentIs there a VoluntaryOrganisation for supportfor Elder people in yourcity? DependentCountry DependentIs there a VoluntaryOrganisation for supportfor Elder people in yourcity? DependentSymmetricCountry DependentIs there a VoluntaryOrganisation for supportfor Elder people in yourcity? DependentSymmetricCountry DependentIs there a VoluntaryOrganisation for supportfor Elder people in yourcity? DependentCountry DependentIs there a VoluntaryOrganisation for supportfor Elder people in yourcity? Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.584 .000

.413 .000

.504 .000

.039 .050 .789 .430

.039 .049 .789 .430

.058 .073 .789 .430

.054 .058 .881 .379c

.032 .050 .513 .609c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Is there a Voluntary

Yes

No

Country * Are you interested in developing of the idea to establish a Centre for Elder people?

Crosstab

6 7 14 274.7 17.7 4.7 27.0

22.2% 25.9% 51.9% 100.0%

13.0% 4.0% 30.4% 10.2%

2.3% 2.6% 5.3% 10.2%1.3 -10.7 9.3.6 -2.5 4.3.7 -4.6 5.00 38 5 43

7.4 28.1 7.4 43.0.0% 88.4% 11.6% 100.0%

.0% 21.8% 10.9% 16.2%

.0% 14.3% 1.9% 16.2%-7.4 9.9 -2.4-2.7 1.9 -.9-3.3 3.5 -1.1

35 46 15 9616.6 62.8 16.6 96.0

36.5% 47.9% 15.6% 100.0%

76.1% 26.4% 32.6% 36.1%

13.2% 17.3% 5.6% 36.1%18.4 -16.8 -1.64.5 -2.1 -.46.2 -4.5 -.5

5 83 11 9917.1 64.8 17.1 99.0

5.1% 83.8% 11.1% 100.0%

10.9% 47.7% 23.9% 37.2%

1.9% 31.2% 4.1% 37.2%-12.1 18.2 -6.1-2.9 2.3 -1.5-4.1 4.9 -2.1

0 0 1 1.2 .7 .2 1.0

.0% .0% 100.0% 100.0%

.0% .0% 2.2% .4%

.0% .0% .4% .4%-.2 -.7 .8-.4 -.8 2.0-.5 -1.4 2.246 174 46 266

46.0 174.0 46.0 266.017.3% 65.4% 17.3% 100.0%

100.0% 100.0% 100.0% 100.0%

17.3% 65.4% 17.3% 100.0%

CountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are youinterested in developingof the idea to establish aCentre for Elder people?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Are you interested in developing ofthe idea to establish a Centre for

Elder people?Total

Chi-Square Tests

82.887a 8 .00082.887 8 .000

.014 1 .906

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (33.3%) have expected count less than 5. The minimumexpected count is .17.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.162 .031 4.656 .000

.204 .043 4.330 .000

.087 .049 1.715 .086

.105 .023 .000c

.176 .036 .000c

.144 .027 5.220 .000d

.121 .023 5.220 .000d

.176 .033 5.220 .000d

.032 .054 .589 .556

.038 .064 .589 .556

.028 .047 .589 .556

.245

.358

SymmetricCountry DependentAre you interested indeveloping of the idea toestablish a Centre forElder people? DependentCountry DependentAre you interested indeveloping of the idea toestablish a Centre forElder people? DependentSymmetricCountry DependentAre you interested indeveloping of the idea toestablish a Centre forElder people? DependentSymmetricCountry DependentAre you interested indeveloping of the idea toestablish a Centre forElder people? DependentCountry DependentAre you interested indeveloping of the idea toestablish a Centre forElder people? Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.558 .000

.395 .000

.487 .000

.032 .055 .589 .556

.029 .049 .589 .556

.051 .086 .589 .556

.040 .062 .645 .520c

-.007 .058 -.117 .907c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

Are you interested i

Yes

No

Country * Are there enough opportunities for entertainment and participating in activities in your area?

Crosstab

6 9 12 274.6 6.8 15.6 27.0

22.2% 33.3% 44.4% 100.0%

13.3% 13.4% 7.8% 10.2%

2.3% 3.4% 4.5% 10.2%1.4 2.2 -3.6.7 .8 -.9.8 1.0 -1.50 5 38 43

7.3 10.8 24.9 43.0.0% 11.6% 88.4% 100.0%

.0% 7.5% 24.7% 16.2%

.0% 1.9% 14.3% 16.2%-7.3 -5.8 13.1-2.7 -1.8 2.6-3.2 -2.2 4.4

33 42 21 9616.2 24.2 55.6 96.0

34.4% 43.8% 21.9% 100.0%

73.3% 62.7% 13.6% 36.1%

12.4% 15.8% 7.9% 36.1%16.8 17.8 -34.64.2 3.6 -4.65.7 5.2 -8.9

6 11 82 9916.7 24.9 57.3 99.0

6.1% 11.1% 82.8% 100.0%

13.3% 16.4% 53.2% 37.2%

2.3% 4.1% 30.8% 37.2%-10.7 -13.9 24.7-2.6 -2.8 3.3-3.6 -4.1 6.3

0 0 1 1.2 .3 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .6% .4%

.0% .0% .4% .4%-.2 -.3 .4-.4 -.5 .6-.5 -.6 .945 67 154 266

45.0 67.0 154.0 266.016.9% 25.2% 57.9% 100.0%

100.0% 100.0% 100.0% 100.0%

16.9% 25.2% 57.9% 100.0%

CountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Are thereenough opportunitiesfor entertainment andparticipating inactivities in your area?% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

Are there enough opportunities forentertainment and participating in

activities in your area?Total

Chi-Square Tests

97.301a 8 .000108.184 8 .000

2.952 1 .086

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .17.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.283 .046 5.381 .000

.347 .046 6.511 .000

.188 .064 2.681 .007

.169 .030 .000c

.230 .036 .000c

.181 .029 6.264 .000d

.158 .026 6.264 .000d

.211 .033 6.264 .000d

-.169 .053 -3.191 .001-.187 .059 -3.191 .001

-.154 .049 -3.191 .001

.154

.500

SymmetricCountry DependentAre there enoughopportunities forentertainment andparticipating in activities inyour area? DependentCountry DependentAre there enoughopportunities forentertainment andparticipating in activities inyour area? DependentSymmetricCountry DependentAre there enoughopportunities forentertainment andparticipating in activities inyour area? DependentSymmetricCountry DependentAre there enoughopportunities forentertainment andparticipating in activities inyour area? DependentCountry DependentAre there enoughopportunities forentertainment andparticipating in activities inyour area? Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.605 .000

.428 .000

.518 .000-.170 .054 -3.191 .001-.161 .050 -3.191 .001-.246 .076 -3.191 .001

-.193 .060 -3.200 .002c

-.106 .054 -1.724 .086c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

100

80

60

40

20

0

Are there enough opp

Yes

No

Country * A centre for older people I would like to offer to me a better health care

Crosstab

6 0 1 5 11 4 272.6 1.1 .4 1.5 9.8 11.5 27.0

22.2% .0% 3.7% 18.5% 40.7% 14.8% 100.0%

23.1% .0% 25.0% 33.3% 11.3% 3.5% 10.2%

2.3% .0% .4% 1.9% 4.1% 1.5% 10.2%3.4 -1.1 .6 3.5 1.2 -7.52.1 -1.1 .9 2.8 .4 -2.22.3 -1.1 1.0 3.1 .5 -3.1

0 0 0 1 31 11 434.2 1.8 .6 2.4 15.7 18.3 43.0

.0% .0% .0% 2.3% 72.1% 25.6% 100.0%

.0% .0% .0% 6.7% 32.0% 9.7% 16.2%

.0% .0% .0% .4% 11.7% 4.1% 16.2%-4.2 -1.8 -.6 -1.4 15.3 -7.3-2.1 -1.3 -.8 -.9 3.9 -1.7-2.4 -1.5 -.9 -1.0 5.3 -2.4

15 8 2 5 38 28 969.4 4.0 1.4 5.4 35.0 40.8 96.0

15.6% 8.3% 2.1% 5.2% 39.6% 29.2% 100.0%

57.7% 72.7% 50.0% 33.3% 39.2% 24.8% 36.1%

5.6% 3.0% .8% 1.9% 14.3% 10.5% 36.1%5.6 4.0 .6 -.4 3.0 -12.81.8 2.0 .5 -.2 .5 -2.02.4 2.6 .6 -.2 .8 -3.3

5 2 1 4 17 70 999.7 4.1 1.5 5.6 36.1 42.1 99.0

5.1% 2.0% 1.0% 4.0% 17.2% 70.7% 100.0%

19.2% 18.2% 25.0% 26.7% 17.5% 61.9% 37.2%

1.9% .8% .4% 1.5% 6.4% 26.3% 37.2%-4.7 -2.1 -.5 -1.6 -19.1 27.9-1.5 -1.0 -.4 -.7 -3.2 4.3-2.0 -1.3 -.5 -.9 -5.0 7.2

0 1 0 0 0 0 1.1 .0 .0 .1 .4 .4 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 9.1% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.1 1.0 .0 -.1 -.4 -.4-.3 4.7 -.1 -.2 -.6 -.7-.3 4.8 -.1 -.2 -.8 -.926 11 4 15 97 113 266

26.0 11.0 4.0 15.0 97.0 113.0 266.09.8% 4.1% 1.5% 5.6% 36.5% 42.5% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

9.8% 4.1% 1.5% 5.6% 36.5% 42.5% 100.0%

CountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me a better health care% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me a better health care

Total

Chi-Square Tests

112.287a 20 .00097.019 20 .000

7.648 1 .006

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

18 cells (60.0%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.241 .046 4.646 .000

.234 .052 4.082 .000

.248 .063 3.490 .000

.122 .026 .000c

.144 .030 .000c

.140 .025 5.453 .000d

.142 .025 5.453 .000d

.139 .025 5.453 .000d

-.296 .050 -6.026 .000-.301 .052 -6.026 .000

-.291 .049 -6.026 .000

.412

.341

SymmetricCountry DependentA centre for olderpeople I would like tooffer to me a betterhealth care DependentCountry DependentA centre for olderpeople I would like tooffer to me a betterhealth care DependentSymmetricCountry DependentA centre for olderpeople I would like tooffer to me a betterhealth care DependentSymmetricCountry DependentA centre for olderpeople I would like tooffer to me a betterhealth care DependentCountry DependentA centre for olderpeople I would like tooffer to me a betterhealth care Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.650 .000

.325 .000

.545 .000-.296 .050 -6.026 .000-.253 .042 -6.026 .000-.408 .066 -6.026 .000

-.345 .057 -5.965 .000c

-.170 .060 -2.801 .005c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * A centre for older people I would like to offer to me lectures/presentations related to popular interests

Crosstab

8 0 0 1 14 4 276.0 .5 .9 5.0 8.1 6.5 27.0

29.6% .0% .0% 3.7% 51.9% 14.8% 100.0%

13.6% .0% .0% 2.0% 17.5% 6.3% 10.2%

3.0% .0% .0% .4% 5.3% 1.5% 10.2%2.0 -.5 -.9 -4.0 5.9 -2.5.8 -.7 -1.0 -1.8 2.1 -1.0

1.0 -.8 -1.0 -2.1 2.6 -1.20 0 2 20 14 7 43

9.5 .8 1.5 7.9 12.9 10.3 43.0.0% .0% 4.7% 46.5% 32.6% 16.3% 100.0%

.0% .0% 22.2% 40.8% 17.5% 10.9% 16.2%

.0% .0% .8% 7.5% 5.3% 2.6% 16.2%-9.5 -.8 .5 12.1 1.1 -3.3-3.1 -.9 .5 4.3 .3 -1.0-3.8 -1.0 .5 5.2 .4 -1.3

45 2 4 20 19 6 9621.3 1.8 3.2 17.7 28.9 23.1 96.0

46.9% 2.1% 4.2% 20.8% 19.8% 6.3% 100.0%

76.3% 40.0% 44.4% 40.8% 23.8% 9.4% 36.1%

16.9% .8% 1.5% 7.5% 7.1% 2.3% 36.1%23.7 .2 .8 2.3 -9.9 -17.15.1 .1 .4 .6 -1.8 -3.67.3 .2 .5 .8 -2.7 -5.1

6 2 3 8 33 47 9922.0 1.9 3.3 18.2 29.8 23.8 99.0

6.1% 2.0% 3.0% 8.1% 33.3% 47.5% 100.0%

10.2% 40.0% 33.3% 16.3% 41.3% 73.4% 37.2%

2.3% .8% 1.1% 3.0% 12.4% 17.7% 37.2%-16.0 .1 -.3 -10.2 3.2 23.2-3.4 .1 -.2 -2.4 .6 4.7-4.9 .1 -.2 -3.3 .9 6.9

0 1 0 0 0 0 1.2 .0 .0 .2 .3 .2 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 20.0% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.2 1.0 .0 -.2 -.3 -.2-.5 7.2 -.2 -.4 -.5 -.5-.5 7.2 -.2 -.5 -.7 -.659 5 9 49 80 64 266

59.0 5.0 9.0 49.0 80.0 64.0 266.022.2% 1.9% 3.4% 18.4% 30.1% 24.1% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

22.2% 1.9% 3.4% 18.4% 30.1% 24.1% 100.0%

CountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to melectures/presentationsrelated to popularinterests% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me lectures/presentationsrelated to popular interests

Total

Chi-Square Tests

176.051a 20 .000139.634 20 .000

5.529 1 .019

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

15 cells (50.0%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.280 .045 5.550 .000

.311 .046 5.971 .000

.253 .062 3.597 .000

.198 .031 .000c

.139 .023 .000c

.186 .026 6.917 .000d

.205 .029 6.917 .000d

.171 .024 6.917 .000d

-.223 .050 -4.552 .000-.212 .047 -4.552 .000

-.234 .053 -4.552 .000

.320

.525

SymmetricCountry DependentA centre for older people Iwould like to offer to melectures/presentationsrelated to popularinterests DependentCountry DependentA centre for older people Iwould like to offer to melectures/presentationsrelated to popularinterests DependentSymmetricCountry DependentA centre for older people Iwould like to offer to melectures/presentationsrelated to popularinterests DependentSymmetricCountry DependentA centre for older people Iwould like to offer to melectures/presentationsrelated to popularinterests DependentCountry DependentA centre for older people Iwould like to offer to melectures/presentationsrelated to popularinterests Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.814 .000

.407 .000

.631 .000-.223 .050 -4.552 .000-.203 .045 -4.552 .000-.289 .064 -4.552 .000

-.285 .059 -4.837 .000c

-.144 .055 -2.372 .018c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * A centre for older people I would like to offer to me visits/trips

Crosstab

4 0 0 3 14 6 274.6 .5 1.5 2.4 9.3 8.6 27.0

14.8% .0% .0% 11.1% 51.9% 22.2% 100.0%

8.9% .0% .0% 12.5% 15.2% 7.1% 10.2%

1.5% .0% .0% 1.1% 5.3% 2.3% 10.2%-.6 -.5 -1.5 .6 4.7 -2.6-.3 -.7 -1.2 .4 1.5 -.9-.3 -.8 -1.3 .4 2.0 -1.1

0 0 3 6 22 12 437.3 .8 2.4 3.9 14.9 13.7 43.0

.0% .0% 7.0% 14.0% 51.2% 27.9% 100.0%

.0% .0% 20.0% 25.0% 23.9% 14.1% 16.2%

.0% .0% 1.1% 2.3% 8.3% 4.5% 16.2%-7.3 -.8 .6 2.1 7.1 -1.7-2.7 -.9 .4 1.1 1.8 -.5-3.2 -1.0 .4 1.2 2.5 -.6

37 3 7 8 29 12 9616.2 1.8 5.4 8.7 33.2 30.7 96.0

38.5% 3.1% 7.3% 8.3% 30.2% 12.5% 100.0%

82.2% 60.0% 46.7% 33.3% 31.5% 14.1% 36.1%

13.9% 1.1% 2.6% 3.0% 10.9% 4.5% 36.1%20.8 1.2 1.6 -.7 -4.2 -18.75.2 .9 .7 -.2 -.7 -3.47.1 1.1 .9 -.3 -1.1 -5.1

4 2 5 6 27 55 9916.7 1.9 5.6 8.9 34.2 31.6 99.0

4.0% 2.0% 5.1% 6.1% 27.3% 55.6% 100.0%

8.9% 40.0% 33.3% 25.0% 29.3% 64.7% 37.2%

1.5% .8% 1.9% 2.3% 10.2% 20.7% 37.2%-12.7 .1 -.6 -2.9 -7.2 23.4-3.1 .1 -.2 -1.0 -1.2 4.2-4.3 .1 -.3 -1.3 -1.9 6.4

0 0 0 1 0 0 1.2 .0 .1 .1 .3 .3 1.0

.0% .0% .0% 100.0% .0% .0% 100.0%

.0% .0% .0% 4.2% .0% .0% .4%

.0% .0% .0% .4% .0% .0% .4%-.2 .0 -.1 .9 -.3 -.3-.4 -.1 -.2 3.0 -.6 -.6-.5 -.1 -.2 3.2 -.7 -.745 5 15 24 92 85 266

45.0 5.0 15.0 24.0 92.0 85.0 266.016.9% 1.9% 5.6% 9.0% 34.6% 32.0% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

16.9% 1.9% 5.6% 9.0% 34.6% 32.0% 100.0%

CountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I would liketo offer to me visits/trips% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me visits/trips

Total

Chi-Square Tests

97.727a 20 .00099.359 20 .000

1.829 1 .176

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

15 cells (50.0%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.226 .049 4.273 .000

.240 .059 3.622 .000

.213 .062 3.085 .002

.152 .027 .000c

.107 .023 .000c

.135 .022 5.950 .000d

.146 .024 5.950 .000d

.126 .021 5.950 .000d

-.177 .048 -3.734 .000-.172 .047 -3.734 .000

-.183 .050 -3.734 .000

.274

.489

SymmetricCountry DependentA centre for older peopleI would like to offer to mevisits/trips DependentCountry DependentA centre for older peopleI would like to offer to mevisits/trips DependentSymmetricCountry DependentA centre for older peopleI would like to offer to mevisits/trips DependentSymmetricCountry DependentA centre for older peopleI would like to offer to mevisits/trips DependentCountry DependentA centre for older peopleI would like to offer to mevisits/trips Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.606 .000

.303 .000

.518 .000-.178 .048 -3.734 .000-.159 .043 -3.734 .000-.238 .064 -3.734 .000

-.223 .059 -3.717 .000c

-.083 .049 -1.355 .177c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * A centre for older people I would like to offer to me entertainment opportunities

Crosstab

6 0 0 1 15 5 276.0 .6 1.2 2.9 5.9 10.4 27.0

22.2% .0% .0% 3.7% 55.6% 18.5% 100.0%

10.2% .0% .0% 3.4% 25.9% 4.9% 10.2%

2.3% .0% .0% .4% 5.6% 1.9% 10.2%.0 -.6 -1.2 -1.9 9.1 -5.4.0 -.8 -1.1 -1.1 3.8 -1.7.0 -.8 -1.2 -1.3 4.5 -2.20 0 1 3 10 29 43

9.5 1.0 1.9 4.7 9.4 16.5 43.0.0% .0% 2.3% 7.0% 23.3% 67.4% 100.0%

.0% .0% 8.3% 10.3% 17.2% 28.4% 16.2%

.0% .0% .4% 1.1% 3.8% 10.9% 16.2%-9.5 -1.0 -.9 -1.7 .6 12.5-3.1 -1.0 -.7 -.8 .2 3.1-3.8 -1.1 -.8 -.9 .3 4.3

50 3 8 17 14 4 9621.3 2.2 4.3 10.5 20.9 36.8 96.0

52.1% 3.1% 8.3% 17.7% 14.6% 4.2% 100.0%

84.7% 50.0% 66.7% 58.6% 24.1% 3.9% 36.1%

18.8% 1.1% 3.0% 6.4% 5.3% 1.5% 36.1%28.7 .8 3.7 6.5 -6.9 -32.86.2 .6 1.8 2.0 -1.5 -5.48.8 .7 2.3 2.7 -2.1 -8.6

3 3 3 7 19 64 9922.0 2.2 4.5 10.8 21.6 38.0 99.0

3.0% 3.0% 3.0% 7.1% 19.2% 64.6% 100.0%

5.1% 50.0% 25.0% 24.1% 32.8% 62.7% 37.2%

1.1% 1.1% 1.1% 2.6% 7.1% 24.1% 37.2%-19.0 .8 -1.5 -3.8 -2.6 26.0-4.0 .5 -.7 -1.2 -.6 4.2-5.8 .7 -.9 -1.5 -.8 6.8

0 0 0 1 0 0 1.2 .0 .0 .1 .2 .4 1.0

.0% .0% .0% 100.0% .0% .0% 100.0%

.0% .0% .0% 3.4% .0% .0% .4%

.0% .0% .0% .4% .0% .0% .4%-.2 .0 .0 .9 -.2 -.4-.5 -.2 -.2 2.7 -.5 -.6-.5 -.2 -.2 2.9 -.5 -.859 6 12 29 58 102 266

59.0 6.0 12.0 29.0 58.0 102.0 266.022.2% 2.3% 4.5% 10.9% 21.8% 38.3% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

22.2% 2.3% 4.5% 10.9% 21.8% 38.3% 100.0%

CountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me entertainmentopportunities% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me entertainment opportunities

Total

Chi-Square Tests

163.630a 20 .000181.101 20 .000

2.374 1 .123

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

16 cells (53.3%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.360 .037 8.216 .000

.371 .045 7.229 .000

.348 .043 7.194 .000

.255 .029 .000c

.217 .029 .000c

.245 .027 9.111 .000d

.265 .029 9.111 .000d

.227 .026 9.111 .000d

-.162 .051 -3.252 .001-.157 .049 -3.252 .001

-.168 .053 -3.252 .001

.262

.660

SymmetricCountry DependentA centre for older people Iwould like to offer to meentertainmentopportunities DependentCountry DependentA centre for older people Iwould like to offer to meentertainmentopportunities DependentSymmetricCountry DependentA centre for older people Iwould like to offer to meentertainmentopportunities DependentSymmetricCountry DependentA centre for older people Iwould like to offer to meentertainmentopportunities DependentCountry DependentA centre for older people Iwould like to offer to meentertainmentopportunities Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.784 .000

.392 .000

.617 .000-.162 .051 -3.252 .001-.146 .045 -3.252 .001-.208 .065 -3.252 .001

-.197 .063 -3.272 .001c

-.095 .051 -1.545 .124c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * A centre for older people I would like to offer to me opportunities for increasing activities

Crosstab

6 0 0 0 18 3 276.1 .6 .6 2.5 8.4 8.7 27.0

22.2% .0% .0% .0% 66.7% 11.1% 100.0%

10.0% .0% .0% .0% 21.7% 3.5% 10.2%

2.3% .0% .0% .0% 6.8% 1.1% 10.2%-.1 -.6 -.6 -2.5 9.6 -5.7.0 -.8 -.8 -1.6 3.3 -1.9.0 -.8 -.8 -1.8 4.2 -2.50 0 1 1 22 19 43

9.7 1.0 1.0 4.0 13.4 13.9 43.0.0% .0% 2.3% 2.3% 51.2% 44.2% 100.0%

.0% .0% 16.7% 4.0% 26.5% 22.1% 16.2%

.0% .0% .4% .4% 8.3% 7.1% 16.2%-9.7 -1.0 .0 -3.0 8.6 5.1-3.1 -1.0 .0 -1.5 2.3 1.4-3.9 -1.1 .0 -1.7 3.1 1.8

49 3 1 16 23 4 9621.7 2.2 2.2 9.0 30.0 31.0 96.0

51.0% 3.1% 1.0% 16.7% 24.0% 4.2% 100.0%

81.7% 50.0% 16.7% 64.0% 27.7% 4.7% 36.1%

18.4% 1.1% .4% 6.0% 8.6% 1.5% 36.1%27.3 .8 -1.2 7.0 -7.0 -27.05.9 .6 -.8 2.3 -1.3 -4.98.4 .7 -1.0 3.1 -1.9 -7.4

5 2 4 8 20 60 9922.3 2.2 2.2 9.3 30.9 32.0 99.0

5.1% 2.0% 4.0% 8.1% 20.2% 60.6% 100.0%

8.3% 33.3% 66.7% 32.0% 24.1% 69.8% 37.2%

1.9% .8% 1.5% 3.0% 7.5% 22.6% 37.2%-17.3 -.2 1.8 -1.3 -10.9 28.0-3.7 -.2 1.2 -.4 -2.0 4.9-5.3 -.2 1.5 -.6 -3.0 7.6

0 1 0 0 0 0 1.2 .0 .0 .1 .3 .3 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 16.7% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.2 1.0 .0 -.1 -.3 -.3-.5 6.5 -.2 -.3 -.6 -.6-.5 6.6 -.2 -.3 -.7 -.760 6 6 25 83 86 266

60.0 6.0 6.0 25.0 83.0 86.0 266.022.6% 2.3% 2.3% 9.4% 31.2% 32.3% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

22.6% 2.3% 2.3% 9.4% 31.2% 32.3% 100.0%

CountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre for olderpeople I would like to offerto me opportunities forincreasing activities% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me opportunities for increasingactivities

Total

Chi-Square Tests

191.474a 20 .000174.306 20 .000

1.743 1 .187

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

16 cells (53.3%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.346 .041 7.097 .000

.335 .055 5.240 .000

.356 .048 6.381 .000

.245 .031 .000c

.201 .028 .000c

.239 .028 8.454 .000d

.255 .029 8.454 .000d

.225 .027 8.454 .000d

-.170 .051 -3.390 .001-.165 .049 -3.390 .001

-.175 .053 -3.390 .001

.389

.599

SymmetricCountry DependentA centre for older peopleI would like to offer tome opportunities forincreasing activitiesDependentCountry DependentA centre for older peopleI would like to offer tome opportunities forincreasing activitiesDependentSymmetricCountry DependentA centre for older peopleI would like to offer tome opportunities forincreasing activitiesDependentSymmetricCountry DependentA centre for older peopleI would like to offer tome opportunities forincreasing activitiesDependentCountry DependentA centre for older peopleI would like to offer tome opportunities forincreasing activitiesDependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.848 .000

.424 .000

.647 .000-.170 .051 -3.390 .001-.152 .045 -3.390 .001-.220 .066 -3.390 .001

-.215 .062 -3.578 .000c

-.081 .051 -1.322 .187c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * A centre for older people I would like to offer to me food

Crosstab

11 0 2 2 9 3 277.8 1.1 2.2 3.8 6.5 5.6 27.0

40.7% .0% 7.4% 7.4% 33.3% 11.1% 100.0%

14.3% .0% 9.1% 5.4% 14.1% 5.5% 10.2%

4.1% .0% .8% .8% 3.4% 1.1% 10.2%3.2 -1.1 -.2 -1.8 2.5 -2.61.1 -1.1 -.2 -.9 1.0 -1.11.4 -1.1 -.2 -1.0 1.2 -1.3

0 2 3 1 30 7 4312.4 1.8 3.6 6.0 10.3 8.9 43.0.0% 4.7% 7.0% 2.3% 69.8% 16.3% 100.0%

.0% 18.2% 13.6% 2.7% 46.9% 12.7% 16.2%

.0% .8% 1.1% .4% 11.3% 2.6% 16.2%-12.4 .2 -.6 -5.0 19.7 -1.9-3.5 .2 -.3 -2.0 6.1 -.6-4.6 .2 -.3 -2.4 7.7 -.8

58 1 6 18 9 4 9627.8 4.0 7.9 13.4 23.1 19.8 96.0

60.4% 1.0% 6.3% 18.8% 9.4% 4.2% 100.0%

75.3% 9.1% 27.3% 48.6% 14.1% 7.3% 36.1%

21.8% .4% 2.3% 6.8% 3.4% 1.5% 36.1%30.2 -3.0 -1.9 4.6 -14.1 -15.85.7 -1.5 -.7 1.3 -2.9 -3.68.5 -1.9 -.9 1.7 -4.2 -5.0

8 8 11 15 16 41 9928.7 4.1 8.2 13.8 23.8 20.5 99.0

8.1% 8.1% 11.1% 15.2% 16.2% 41.4% 100.0%

10.4% 72.7% 50.0% 40.5% 25.0% 74.5% 37.2%

3.0% 3.0% 4.1% 5.6% 6.0% 15.4% 37.2%-20.7 3.9 2.8 1.2 -7.8 20.5-3.9 1.9 1.0 .3 -1.6 4.5-5.8 2.5 1.3 .5 -2.3 6.4

0 0 0 1 0 0 1.3 .0 .1 .1 .2 .2 1.0

.0% .0% .0% 100.0% .0% .0% 100.0%

.0% .0% .0% 2.7% .0% .0% .4%

.0% .0% .0% .4% .0% .0% .4%-.3 .0 -.1 .9 -.2 -.2-.5 -.2 -.3 2.3 -.5 -.5-.6 -.2 -.3 2.5 -.6 -.577 11 22 37 64 55 266

77.0 11.0 22.0 37.0 64.0 55.0 266.028.9% 4.1% 8.3% 13.9% 24.1% 20.7% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

28.9% 4.1% 8.3% 13.9% 24.1% 20.7% 100.0%

CountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within A centre forolder people I wouldlike to offer to me food% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

A centre for older people I would like to offer to me food

Total

Chi-Square Tests

167.324a 20 .000170.835 20 .000

3.442 1 .064

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

13 cells (43.3%) have expected count less than 5. The minimumexpected count is .04.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.368 .041 8.519 .000

.401 .056 5.919 .000

.339 .038 7.963 .000

.251 .035 .000c

.187 .027 .000c

.220 .027 8.070 .000d

.250 .031 8.070 .000d

.196 .025 8.070 .000d

-.132 .052 -2.589 .010-.125 .048 -2.589 .010

-.141 .056 -2.589 .010

.400

.581

SymmetricCountry DependentA centre for older peopleI would like to offer to mefood DependentCountry DependentA centre for older peopleI would like to offer to mefood DependentSymmetricCountry DependentA centre for older peopleI would like to offer to mefood DependentSymmetricCountry DependentA centre for older peopleI would like to offer to mefood DependentCountry DependentA centre for older peopleI would like to offer to mefood Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.793 .000

.397 .000

.621 .000-.133 .052 -2.589 .010-.123 .047 -2.589 .010-.167 .065 -2.589 .010

-.169 .063 -2.782 .006c

-.114 .057 -1.864 .063c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

A centre for older p

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * Elderly people don't need lectures, theatrical plays and trips, they only need caring and food.

Crosstab

3 11 10 1 2 0 273.0 9.2 8.4 2.3 2.6 1.3 27.0

11.1% 40.7% 37.0% 3.7% 7.4% .0% 100.0%

10.0% 12.1% 12.0% 4.3% 7.7% .0% 10.2%

1.1% 4.1% 3.8% .4% .8% .0% 10.2%.0 1.8 1.6 -1.3 -.6 -1.3.0 .6 .5 -.9 -.4 -1.1.0 .8 .7 -1.0 -.4 -1.20 5 19 5 8 6 43

4.8 14.7 13.4 3.7 4.2 2.1 43.0.0% 11.6% 44.2% 11.6% 18.6% 14.0% 100.0%

.0% 5.5% 22.9% 21.7% 30.8% 46.2% 16.2%

.0% 1.9% 7.1% 1.9% 3.0% 2.3% 16.2%-4.8 -9.7 5.6 1.3 3.8 3.9-2.2 -2.5 1.5 .7 1.9 2.7-2.6 -3.4 2.0 .8 2.1 3.0

24 21 32 10 7 2 9610.8 32.8 30.0 8.3 9.4 4.7 96.0

25.0% 21.9% 33.3% 10.4% 7.3% 2.1% 100.0%

80.0% 23.1% 38.6% 43.5% 26.9% 15.4% 36.1%

9.0% 7.9% 12.0% 3.8% 2.6% .8% 36.1%13.2 -11.8 2.0 1.7 -2.4 -2.74.0 -2.1 .4 .6 -.8 -1.25.3 -3.2 .6 .8 -1.0 -1.6

3 53 22 7 9 5 9911.2 33.9 30.9 8.6 9.7 4.8 99.0

3.0% 53.5% 22.2% 7.1% 9.1% 5.1% 100.0%

10.0% 58.2% 26.5% 30.4% 34.6% 38.5% 37.2%

1.1% 19.9% 8.3% 2.6% 3.4% 1.9% 37.2%-8.2 19.1 -8.9 -1.6 -.7 .2-2.4 3.3 -1.6 -.5 -.2 .1-3.3 5.1 -2.4 -.7 -.3 .1

0 1 0 0 0 0 1.1 .3 .3 .1 .1 .0 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 1.1% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.1 .7 -.3 -.1 -.1 .0-.3 1.1 -.6 -.3 -.3 -.2-.4 1.4 -.7 -.3 -.3 -.230 91 83 23 26 13 266

30.0 91.0 83.0 23.0 26.0 13.0 266.011.3% 34.2% 31.2% 8.6% 9.8% 4.9% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

11.3% 34.2% 31.2% 8.6% 9.8% 4.9% 100.0%

CountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderly peopledon't need lectures,theatrical plays andtrips, they only needcaring and food.% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Elderly people don't need lectures, theatrical plays and trips, they only needcaring and food.

Total

Chi-Square Tests

72.088a 20 .00075.520 20 .000

.742 1 .389

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

16 cells (53.3%) have expected count less than 5. The minimumexpected count is .05.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.175 .042 3.902 .000

.210 .056 3.426 .001

.143 .046 2.894 .004

.108 .024 .000c

.069 .017 .000c

.100 .020 5.028 .000d

.111 .022 5.028 .000d

.091 .018 5.028 .000d

.102 .048 2.109 .035

.098 .047 2.109 .035

.106 .050 2.109 .035

.224

.339

SymmetricCountry DependentElderly people don'tneed lectures, theatricalplays and trips, theyonly need caring andfood. DependentCountry DependentElderly people don'tneed lectures, theatricalplays and trips, theyonly need caring andfood. DependentSymmetricCountry DependentElderly people don'tneed lectures, theatricalplays and trips, theyonly need caring andfood. DependentSymmetricCountry DependentElderly people don'tneed lectures, theatricalplays and trips, theyonly need caring andfood. DependentCountry DependentElderly people don'tneed lectures, theatricalplays and trips, theyonly need caring andfood. Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.521 .000

.260 .000

.462 .000

.102 .048 2.109 .035

.092 .044 2.109 .035

.137 .065 2.109 .035

.128 .059 2.105 .036c

.053 .053 .861 .390c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

Elderly people don't

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * Young people need good company more than elderly people.

Crosstab

3 8 13 2 1 0 273.5 8.5 8.6 2.3 3.0 1.0 27.0

11.1% 29.6% 48.1% 7.4% 3.7% .0% 100.0%

8.8% 9.5% 15.3% 8.7% 3.3% .0% 10.2%

1.1% 3.0% 4.9% .8% .4% .0% 10.2%-.5 -.5 4.4 -.3 -2.0 -1.0-.2 -.2 1.5 -.2 -1.2 -1.0-.3 -.2 1.9 -.2 -1.3 -1.1

0 15 20 1 5 2 435.5 13.6 13.7 3.7 4.8 1.6 43.0

.0% 34.9% 46.5% 2.3% 11.6% 4.7% 100.0%

.0% 17.9% 23.5% 4.3% 16.7% 20.0% 16.2%

.0% 5.6% 7.5% .4% 1.9% .8% 16.2%-5.5 1.4 6.3 -2.7 .2 .4-2.3 .4 1.7 -1.4 .1 .3-2.7 .5 2.2 -1.6 .1 .3

28 15 26 9 14 4 9612.3 30.3 30.7 8.3 10.8 3.6 96.0

29.2% 15.6% 27.1% 9.4% 14.6% 4.2% 100.0%

82.4% 17.9% 30.6% 39.1% 46.7% 40.0% 36.1%

10.5% 5.6% 9.8% 3.4% 5.3% 1.5% 36.1%15.7 -15.3 -4.7 .7 3.2 .44.5 -2.8 -.8 .2 1.0 .26.0 -4.2 -1.3 .3 1.3 .3

3 45 26 11 10 4 9912.7 31.3 31.6 8.6 11.2 3.7 99.0

3.0% 45.5% 26.3% 11.1% 10.1% 4.0% 100.0%

8.8% 53.6% 30.6% 47.8% 33.3% 40.0% 37.2%

1.1% 16.9% 9.8% 4.1% 3.8% 1.5% 37.2%-9.7 13.7 -5.6 2.4 -1.2 .3-2.7 2.5 -1.0 .8 -.3 .1-3.7 3.7 -1.5 1.1 -.5 .2

0 1 0 0 0 0 1.1 .3 .3 .1 .1 .0 1.0

.0% 100.0% .0% .0% .0% .0% 100.0%

.0% 1.2% .0% .0% .0% .0% .4%

.0% .4% .0% .0% .0% .0% .4%-.1 .7 -.3 -.1 -.1 .0-.4 1.2 -.6 -.3 -.3 -.2-.4 1.5 -.7 -.3 -.4 -.234 84 85 23 30 10 266

34.0 84.0 85.0 23.0 30.0 10.0 266.012.8% 31.6% 32.0% 8.6% 11.3% 3.8% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

12.8% 31.6% 32.0% 8.6% 11.3% 3.8% 100.0%

CountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Young peopleneed good companymore than elderly people.% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Young people need good company more than elderly people.

Total

Chi-Square Tests

62.377a 20 .00068.586 20 .000

.311 1 .577

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

15 cells (50.0%) have expected count less than 5. The minimumexpected count is .04.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.147 .041 3.383 .001

.174 .040 4.028 .000

.122 .058 1.974 .048

.100 .022 .000c

.059 .015 .000c

.090 .018 4.976 .000d

.100 .020 4.976 .000d

.082 .016 4.976 .000d

-.002 .043 -.055 .956-.002 .042 -.055 .956

-.002 .045 -.055 .956

.201

.201

SymmetricCountry DependentYoung people needgood companymore than elderlypeople. DependentCountry DependentYoung people needgood companymore than elderlypeople. DependentSymmetricCountry DependentYoung people needgood companymore than elderlypeople. DependentSymmetricCountry DependentYoung people needgood companymore than elderlypeople. DependentCountry DependentYoung people needgood companymore than elderlypeople. Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.484 .000

.242 .000

.436 .000-.002 .043 -.055 .956-.002 .039 -.055 .956-.003 .059 -.055 .956

.001 .054 .017 .986c

-.034 .047 -.557 .578c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Young people need go

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * People, in spite of their age, want to learn and be active.

Crosstab

4 0 1 0 15 7 273.2 .5 1.0 2.6 9.2 10.4 27.0

14.8% .0% 3.7% .0% 55.6% 25.9% 100.0%

12.5% .0% 10.0% .0% 16.5% 6.9% 10.2%

1.5% .0% .4% .0% 5.6% 2.6% 10.2%.8 -.5 .0 -2.6 5.8 -3.4.4 -.7 .0 -1.6 1.9 -1.0.5 -.8 .0 -1.8 2.5 -1.40 1 7 4 15 16 43

5.2 .8 1.6 4.2 14.7 16.5 43.0.0% 2.3% 16.3% 9.3% 34.9% 37.2% 100.0%

.0% 20.0% 70.0% 15.4% 16.5% 15.7% 16.2%

.0% .4% 2.6% 1.5% 5.6% 6.0% 16.2%-5.2 .2 5.4 -.2 .3 -.5-2.3 .2 4.2 -.1 .1 -.1-2.6 .2 4.7 -.1 .1 -.2

25 2 1 19 37 12 9611.5 1.8 3.6 9.4 32.8 36.8 96.0

26.0% 2.1% 1.0% 19.8% 38.5% 12.5% 100.0%

78.1% 40.0% 10.0% 73.1% 40.7% 11.8% 36.1%

9.4% .8% .4% 7.1% 13.9% 4.5% 36.1%13.5 .2 -2.6 9.6 4.2 -24.84.0 .1 -1.4 3.1 .7 -4.15.3 .2 -1.8 4.1 1.1 -6.5

3 2 1 3 23 67 9911.9 1.9 3.7 9.7 33.9 38.0 99.0

3.0% 2.0% 1.0% 3.0% 23.2% 67.7% 100.0%

9.4% 40.0% 10.0% 11.5% 25.3% 65.7% 37.2%

1.1% .8% .4% 1.1% 8.6% 25.2% 37.2%-8.9 .1 -2.7 -6.7 -10.9 29.0-2.6 .1 -1.4 -2.1 -1.9 4.7-3.5 .1 -1.8 -2.9 -2.9 7.6

0 0 0 0 1 0 1.1 .0 .0 .1 .3 .4 1.0

.0% .0% .0% .0% 100.0% .0% 100.0%

.0% .0% .0% .0% 1.1% .0% .4%

.0% .0% .0% .0% .4% .0% .4%-.1 .0 .0 -.1 .7 -.4-.3 -.1 -.2 -.3 1.1 -.6-.4 -.1 -.2 -.3 1.4 -.832 5 10 26 91 102 266

32.0 5.0 10.0 26.0 91.0 102.0 266.012.0% 1.9% 3.8% 9.8% 34.2% 38.3% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

12.0% 1.9% 3.8% 9.8% 34.2% 38.3% 100.0%

CountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within People, inspite of their age, wantto learn and be active.% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

People, in spite of their age, want to learn and be active.

Total

Chi-Square Tests

116.754a 20 .000118.888 20 .000

5.656 1 .017

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

17 cells (56.7%) have expected count less than 5. The minimumexpected count is .02.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.278 .041 6.038 .000

.347 .053 5.651 .000

.207 .046 4.134 .000

.190 .032 .000c

.129 .024 .000c

.166 .025 6.410 .000d

.174 .027 6.410 .000d

.158 .024 6.410 .000d

-.256 .050 -5.255 .000-.253 .049 -5.255 .000

-.258 .051 -5.255 .000

.315

.421

SymmetricCountry DependentPeople, in spite of theirage, want to learn andbe active. DependentCountry DependentPeople, in spite of theirage, want to learn andbe active. DependentSymmetricCountry DependentPeople, in spite of theirage, want to learn andbe active. DependentSymmetricCountry DependentPeople, in spite of theirage, want to learn andbe active. DependentCountry DependentPeople, in spite of theirage, want to learn andbe active. Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.663 .000

.331 .000

.552 .000-.256 .050 -5.255 .000-.224 .043 -5.255 .000-.343 .065 -5.255 .000

-.308 .058 -5.258 .000c

-.146 .052 -2.400 .017c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

70

60

50

40

30

20

10

0

People, in spite of

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * Elderly people can enjoy life as younger people do.

Crosstab

4 0 1 1 13 8 272.6 1.0 2.1 1.5 11.6 8.1 27.0

14.8% .0% 3.7% 3.7% 48.1% 29.6% 100.0%

15.4% .0% 4.8% 6.7% 11.4% 10.0% 10.2%

1.5% .0% .4% .4% 4.9% 3.0% 10.2%1.4 -1.0 -1.1 -.5 1.4 -.1.8 -1.0 -.8 -.4 .4 .0.9 -1.1 -.9 -.5 .6 -.10 1 2 0 18 22 43

4.2 1.6 3.4 2.4 18.4 12.9 43.0.0% 2.3% 4.7% .0% 41.9% 51.2% 100.0%

.0% 10.0% 9.5% .0% 15.8% 27.5% 16.2%

.0% .4% .8% .0% 6.8% 8.3% 16.2%-4.2 -.6 -1.4 -2.4 -.4 9.1-2.1 -.5 -.8 -1.6 -.1 2.5-2.4 -.5 -.9 -1.8 -.1 3.3

19 1 2 4 47 23 969.4 3.6 7.6 5.4 41.1 28.9 96.0

19.8% 1.0% 2.1% 4.2% 49.0% 24.0% 100.0%

73.1% 10.0% 9.5% 26.7% 41.2% 28.8% 36.1%

7.1% .4% .8% 1.5% 17.7% 8.6% 36.1%9.6 -2.6 -5.6 -1.4 5.9 -5.93.1 -1.4 -2.0 -.6 .9 -1.14.1 -1.8 -2.6 -.8 1.5 -1.6

3 8 16 10 35 27 999.7 3.7 7.8 5.6 42.4 29.8 99.0

3.0% 8.1% 16.2% 10.1% 35.4% 27.3% 100.0%

11.5% 80.0% 76.2% 66.7% 30.7% 33.8% 37.2%

1.1% 3.0% 6.0% 3.8% 13.2% 10.2% 37.2%-6.7 4.3 8.2 4.4 -7.4 -2.8-2.1 2.2 2.9 1.9 -1.1 -.5-2.9 2.9 3.8 2.4 -1.9 -.8

0 0 0 0 1 0 1.1 .0 .1 .1 .4 .3 1.0

.0% .0% .0% .0% 100.0% .0% 100.0%

.0% .0% .0% .0% .9% .0% .4%

.0% .0% .0% .0% .4% .0% .4%-.1 .0 -.1 -.1 .6 -.3-.3 -.2 -.3 -.2 .9 -.5-.3 -.2 -.3 -.2 1.2 -.726 10 21 15 114 80 266

26.0 10.0 21.0 15.0 114.0 80.0 266.09.8% 3.8% 7.9% 5.6% 42.9% 30.1% 100.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

9.8% 3.8% 7.9% 5.6% 42.9% 30.1% 100.0%

CountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within Elderlypeople can enjoy lifeas younger people do.% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

MissingStronglydisagree Disagree I am not sure Agree

Stronglyagree

Elderly people can enjoy life as younger people do.

Total

Chi-Square Tests

59.207a 20 .00064.498 20 .000

.940 1 .332

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

16 cells (53.3%) have expected count less than 5. The minimumexpected count is .04.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.100 .035 2.703 .007

.168 .056 2.785 .005

.026 .041 .633 .527

.096 .022 .000c

.040 .012 .000c

.089 .018 4.837 .000d

.094 .019 4.837 .000d

.084 .017 4.837 .000d

.126 .051 2.471 .013

.125 .051 2.471 .013

.127 .051 2.471 .013

.273

.233

SymmetricCountry DependentElderly people canenjoy life as youngerpeople do. DependentCountry DependentElderly people canenjoy life as youngerpeople do. DependentSymmetricCountry DependentElderly people canenjoy life as youngerpeople do. DependentSymmetricCountry DependentElderly people canenjoy life as youngerpeople do. DependentCountry DependentElderly people canenjoy life as youngerpeople do. Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.472 .000

.236 .000

.427 .000

.126 .051 2.471 .013

.110 .045 2.471 .013

.179 .072 2.471 .013

.150 .060 2.458 .015c

.060 .058 .969 .333c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

Elderly people can e

Strongly disagree

Disagree

I am not sure

Agree

Strongly agree

Country * I would like computer lessons

Crosstab

7 11 9 277.0 5.6 14.4 27.0

25.9% 40.7% 33.3% 100.0%

10.1% 20.0% 6.3% 10.2%

2.6% 4.1% 3.4% 10.2%.0 5.4 -5.4.0 2.3 -1.4.0 2.7 -2.20 13 30 43

11.2 8.9 23.0 43.0.0% 30.2% 69.8% 100.0%

.0% 23.6% 21.1% 16.2%

.0% 4.9% 11.3% 16.2%-11.2 4.1 7.0-3.3 1.4 1.5-4.2 1.7 2.4

49 17 30 9624.9 19.8 51.2 96.0

51.0% 17.7% 31.3% 100.0%

71.0% 30.9% 21.1% 36.1%

18.4% 6.4% 11.3% 36.1%24.1 -2.8 -21.24.8 -.6 -3.07.0 -.9 -5.413 13 73 99

25.7 20.5 52.8 99.013.1% 13.1% 73.7% 100.0%

18.8% 23.6% 51.4% 37.2%

4.9% 4.9% 27.4% 37.2%-12.7 -7.5 20.2-2.5 -1.7 2.8-3.7 -2.3 5.1

0 1 0 1.3 .2 .5 1.0

.0% 100.0% .0% 100.0%

.0% 1.8% .0% .4%

.0% .4% .0% .4%-.3 .8 -.5-.5 1.7 -.7-.6 2.0 -1.169 55 142 266

69.0 55.0 142.0 266.025.9% 20.7% 53.4% 100.0%

100.0% 100.0% 100.0% 100.0%

25.9% 20.7% 53.4% 100.0%

CountExpected Count% within Country% within I would likecomputer lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecomputer lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecomputer lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecomputer lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecomputer lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecomputer lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like computer lessons

Total

Chi-Square Tests

75.550a 8 .00082.116 8 .000

1.173 1 .279

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .21.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.213 .052 3.735 .000

.240 .050 4.314 .000

.177 .073 2.220 .026

.115 .026 .000c

.154 .032 .000c

.135 .024 5.536 .000d

.120 .021 5.536 .000d

.153 .027 5.536 .000d

-.140 .050 -2.842 .004-.151 .053 -2.842 .004

-.131 .047 -2.842 .004

.214

.469

SymmetricCountry DependentI would like computerlessons DependentCountry DependentI would like computerlessons DependentSymmetricCountry DependentI would like computerlessons DependentSymmetricCountry DependentI would like computerlessons DependentCountry DependentI would like computerlessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.533 .000

.377 .000

.470 .000-.140 .050 -2.842 .004-.137 .048 -2.842 .004-.203 .071 -2.842 .004

-.167 .058 -2.745 .006c

-.067 .053 -1.083 .280c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I would like compute

Yes

No

Country * I would like cooking lessons

Crosstab

10 5 12 276.7 8.5 11.8 27.0

37.0% 18.5% 44.4% 100.0%

15.2% 6.0% 10.3% 10.2%

3.8% 1.9% 4.5% 10.2%3.3 -3.5 .21.3 -1.2 .11.6 -1.5 .1

0 11 32 4310.7 13.6 18.8 43.0.0% 25.6% 74.4% 100.0%

.0% 13.1% 27.6% 16.2%

.0% 4.1% 12.0% 16.2%-10.7 -2.6 13.2-3.3 -.7 3.1-4.1 -.9 4.4

48 23 25 9623.8 30.3 41.9 96.0

50.0% 24.0% 26.0% 100.0%

72.7% 27.4% 21.6% 36.1%

18.0% 8.6% 9.4% 36.1%24.2 -7.3 -16.95.0 -1.3 -2.67.1 -2.0 -4.3

8 45 46 9924.6 31.3 43.2 99.0

8.1% 45.5% 46.5% 100.0%

12.1% 53.6% 39.7% 37.2%

3.0% 16.9% 17.3% 37.2%-16.6 13.7 2.8-3.3 2.5 .4-4.9 3.7 .7

0 0 1 1.2 .3 .4 1.0

.0% .0% 100.0% 100.0%

.0% .0% .9% .4%

.0% .0% .4% .4%-.2 -.3 .6-.5 -.6 .9-.6 -.7 1.166 84 116 266

66.0 84.0 116.0 266.024.8% 31.6% 43.6% 100.0%

100.0% 100.0% 100.0% 100.0%

24.8% 31.6% 43.6% 100.0%

CountExpected Count% within Country% within I would likecooking lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecooking lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecooking lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecooking lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecooking lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likecooking lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like cooking lessons

Total

Chi-Square Tests

75.397a 8 .00083.811 8 .000

1.302 1 .254

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .25.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.199 .043 4.347 .000

.240 .039 5.658 .000

.153 .052 2.729 .006

.119 .025 .000c

.131 .027 .000c

.134 .023 5.654 .000d

.123 .022 5.654 .000d

.147 .026 5.654 .000d

-.029 .053 -.560 .576-.030 .054 -.560 .576

-.028 .051 -.560 .576

.194

.489

SymmetricCountry DependentI would like cookinglessons DependentCountry DependentI would like cookinglessons DependentSymmetricCountry DependentI would like cookinglessons DependentSymmetricCountry DependentI would like cookinglessons DependentCountry DependentI would like cookinglessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.532 .000

.376 .000

.470 .000-.029 .053 -.560 .576-.030 .053 -.560 .576-.042 .075 -.560 .576

-.026 .062 -.417 .677c

-.070 .057 -1.142 .255c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

50

40

30

20

10

0

I would like cooking

Yes

No

Country * I would like dancing lessons

Crosstab

8 6 13 276.9 5.2 14.9 27.0

29.6% 22.2% 48.1% 100.0%

11.8% 11.8% 8.8% 10.2%

3.0% 2.3% 4.9% 10.2%1.1 .8 -1.9.4 .4 -.5.5 .4 -.80 10 33 43

11.0 8.2 23.8 43.0.0% 23.3% 76.7% 100.0%

.0% 19.6% 22.4% 16.2%

.0% 3.8% 12.4% 16.2%-11.0 1.8 9.2-3.3 .6 1.9-4.2 .7 3.1

48 13 35 9624.5 18.4 53.1 96.0

50.0% 13.5% 36.5% 100.0%

70.6% 25.5% 23.8% 36.1%

18.0% 4.9% 13.2% 36.1%23.5 -5.4 -18.14.7 -1.3 -2.56.9 -1.8 -4.612 22 65 99

25.3 19.0 54.7 99.012.1% 22.2% 65.7% 100.0%

17.6% 43.1% 44.2% 37.2%

4.5% 8.3% 24.4% 37.2%-13.3 3.0 10.3-2.6 .7 1.4-3.9 1.0 2.6

0 0 1 1.3 .2 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .4-.5 -.4 .6-.6 -.5 .968 51 147 266

68.0 51.0 147.0 266.025.6% 19.2% 55.3% 100.0%

100.0% 100.0% 100.0% 100.0%

25.6% 19.2% 55.3% 100.0%

CountExpected Count% within Country% within I would likedancing lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likedancing lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likedancing lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likedancing lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likedancing lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likedancing lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like dancing lessons

Total

Chi-Square Tests

55.887a 8 .00064.501 8 .000

.608 1 .436

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .19.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.171 .050 3.231 .001

.216 .041 4.849 .000

.109 .072 1.432 .152

.091 .023 .000c

.113 .027 .000c

.107 .020 5.148 .000d

.094 .018 5.148 .000d

.122 .023 5.148 .000d

-.068 .050 -1.363 .173-.074 .054 -1.363 .173

-.063 .047 -1.363 .173

.049

.449

SymmetricCountry DependentI would like dancinglessons DependentCountry DependentI would like dancinglessons DependentSymmetricCountry DependentI would like dancinglessons DependentSymmetricCountry DependentI would like dancinglessons DependentCountry DependentI would like dancinglessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.458 .000

.324 .000

.417 .000-.069 .050 -1.363 .173-.066 .048 -1.363 .173-.103 .075 -1.363 .173

-.077 .058 -1.258 .210c

-.048 .055 -.779 .437c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

I would like dancing

Yes

No

Country * I would like art and crafts lessons

Crosstab

8 6 13 276.8 5.0 15.2 27.0

29.6% 22.2% 48.1% 100.0%

11.9% 12.2% 8.7% 10.2%

3.0% 2.3% 4.9% 10.2%1.2 1.0 -2.2.5 .5 -.6.6 .5 -.90 5 38 43

10.8 7.9 24.2 43.0.0% 11.6% 88.4% 100.0%

.0% 10.2% 25.3% 16.2%

.0% 1.9% 14.3% 16.2%-10.8 -2.9 13.8-3.3 -1.0 2.8-4.2 -1.3 4.6

48 20 28 9624.2 17.7 54.1 96.0

50.0% 20.8% 29.2% 100.0%

71.6% 40.8% 18.7% 36.1%

18.0% 7.5% 10.5% 36.1%23.8 2.3 -26.14.8 .6 -3.67.0 .8 -6.711 18 70 99

24.9 18.2 55.8 99.011.1% 18.2% 70.7% 100.0%

16.4% 36.7% 46.7% 37.2%

4.1% 6.8% 26.3% 37.2%-13.9 -.2 14.2-2.8 -.1 1.9-4.1 -.1 3.6

0 0 1 1.3 .2 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .4-.5 -.4 .6-.6 -.5 .967 49 150 266

67.0 49.0 150.0 266.025.2% 18.4% 56.4% 100.0%

100.0% 100.0% 100.0% 100.0%

25.2% 18.4% 56.4% 100.0%

CountExpected Count% within Country% within I would likeart and crafts lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likeart and crafts lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likeart and crafts lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likeart and crafts lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likeart and crafts lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likeart and crafts lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like art and crafts lessons

Total

Chi-Square Tests

69.004a 8 .00078.452 8 .000

.793 1 .373

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .18.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.208 .052 3.688 .000

.234 .052 4.082 .000

.172 .068 2.317 .020

.112 .024 .000c

.161 .032 .000c

.130 .023 5.547 .000d

.115 .021 5.547 .000d

.150 .027 5.547 .000d

-.079 .052 -1.521 .128-.086 .057 -1.521 .128

-.073 .048 -1.521 .128

.055

.497

SymmetricCountry DependentI would like art and craftslessons DependentCountry DependentI would like art and craftslessons DependentSymmetricCountry DependentI would like art and craftslessons DependentSymmetricCountry DependentI would like art and craftslessons DependentCountry DependentI would like art and craftslessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.509 .000

.360 .000

.454 .000-.079 .052 -1.521 .128-.076 .050 -1.521 .128-.118 .077 -1.521 .128

-.088 .060 -1.432 .153c

-.055 .055 -.890 .374c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I would like art and

Yes

No

Country * I would like pottery lessons

Crosstab

10 2 15 278.3 2.3 16.3 27.0

37.0% 7.4% 55.6% 100.0%

12.2% 8.7% 9.3% 10.2%

3.8% .8% 5.6% 10.2%1.7 -.3 -1.3.6 -.2 -.3.7 -.2 -.60 1 42 43

13.3 3.7 26.0 43.0.0% 2.3% 97.7% 100.0%

.0% 4.3% 26.1% 16.2%

.0% .4% 15.8% 16.2%-13.3 -2.7 16.0-3.6 -1.4 3.1-4.8 -1.6 5.4

57 5 34 9629.6 8.3 58.1 96.0

59.4% 5.2% 35.4% 100.0%

69.5% 21.7% 21.1% 36.1%

21.4% 1.9% 12.8% 36.1%27.4 -3.3 -24.15.0 -1.1 -3.27.6 -1.5 -6.315 15 69 99

30.5 8.6 59.9 99.015.2% 15.2% 69.7% 100.0%

18.3% 65.2% 42.9% 37.2%

5.6% 5.6% 25.9% 37.2%-15.5 6.4 9.1-2.8 2.2 1.2-4.3 2.9 2.4

0 0 1 1.3 .1 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .6% .4%

.0% .0% .4% .4%-.3 -.1 .4-.6 -.3 .5-.7 -.3 .882 23 161 266

82.0 23.0 161.0 266.030.8% 8.6% 60.5% 100.0%

100.0% 100.0% 100.0% 100.0%

30.8% 8.6% 60.5% 100.0%

CountExpected Count% within Country% within I wouldlike pottery lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike pottery lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike pottery lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike pottery lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike pottery lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike pottery lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like pottery lessons

Total

Chi-Square Tests

76.999a 8 .00087.261 8 .000

.279 1 .597

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (33.3%) have expected count less than 5. The minimumexpected count is .09.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.239 .054 4.023 .000

.251 .044 5.195 .000

.219 .080 2.438 .015

.122 .026 .000c

.200 .036 .000c

.152 .025 5.930 .000d

.128 .021 5.930 .000d

.187 .031 5.930 .000d

-.033 .052 -.638 .524-.038 .060 -.638 .524

-.029 .046 -.638 .524

.135

.507

SymmetricCountry DependentI would like potterylessons DependentCountry DependentI would like potterylessons DependentSymmetricCountry DependentI would like potterylessons DependentSymmetricCountry DependentI would like potterylessons DependentCountry DependentI would like potterylessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.538 .000

.380 .000

.474 .000-.034 .053 -.638 .524-.031 .048 -.638 .524-.052 .081 -.638 .524

-.031 .060 -.509 .611c

-.032 .056 -.528 .598c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I would like pottery

Yes

No

Country * I would like foreing languages lessons

Crosstab

9 4 14 277.7 4.0 15.3 27.0

33.3% 14.8% 51.9% 100.0%

11.8% 10.3% 9.3% 10.2%

3.4% 1.5% 5.3% 10.2%1.3 .0 -1.3.5 .0 -.3.6 .0 -.50 6 37 43

12.3 6.3 24.4 43.0.0% 14.0% 86.0% 100.0%

.0% 15.4% 24.5% 16.2%

.0% 2.3% 13.9% 16.2%-12.3 -.3 12.6-3.5 -.1 2.5-4.5 -.1 4.2

54 8 34 9627.4 14.1 54.5 96.0

56.3% 8.3% 35.4% 100.0%

71.1% 20.5% 22.5% 36.1%

20.3% 3.0% 12.8% 36.1%26.6 -6.1 -20.55.1 -1.6 -2.87.5 -2.2 -5.313 21 65 99

28.3 14.5 56.2 99.013.1% 21.2% 65.7% 100.0%

17.1% 53.8% 43.0% 37.2%

4.9% 7.9% 24.4% 37.2%-15.3 6.5 8.8-2.9 1.7 1.2-4.3 2.3 2.3

0 0 1 1.3 .1 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.1 .4-.5 -.4 .6-.6 -.4 .976 39 151 266

76.0 39.0 151.0 266.028.6% 14.7% 56.8% 100.0%

100.0% 100.0% 100.0% 100.0%

28.6% 14.7% 56.8% 100.0%

CountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike foreinglanguages lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I would like foreing languageslessons

Total

Chi-Square Tests

68.493a 8 .00077.891 8 .000

.423 1 .515

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .15.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.216 .051 3.866 .000

.246 .043 5.263 .000

.174 .074 2.150 .032

.112 .025 .000c

.152 .032 .000c

.130 .023 5.600 .000d

.114 .020 5.600 .000d

.152 .027 5.600 .000d

-.047 .051 -.916 .360-.051 .056 -.916 .360

-.043 .047 -.916 .360

.078

.489

SymmetricCountry DependentI would like foreinglanguages lessonsDependentCountry DependentI would like foreinglanguages lessonsDependentSymmetricCountry DependentI would like foreinglanguages lessonsDependentSymmetricCountry DependentI would like foreinglanguages lessonsDependentCountry DependentI would like foreinglanguages lessonsDependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.507 .000

.359 .000

.453 .000-.047 .051 -.916 .360-.044 .048 -.916 .360-.070 .077 -.916 .360

-.049 .059 -.793 .428c

-.040 .055 -.650 .516c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

I would like foreing

Yes

No

Country * I would like my countries' language for foreigners

Crosstab

8 4 15 278.5 1.7 16.7 27.0

29.6% 14.8% 55.6% 100.0%

9.5% 23.5% 9.1% 10.2%

3.0% 1.5% 5.6% 10.2%-.5 2.3 -1.7-.2 1.7 -.4-.2 1.9 -.7

0 3 40 4313.6 2.7 26.7 43.0.0% 7.0% 93.0% 100.0%

.0% 17.6% 24.2% 16.2%

.0% 1.1% 15.0% 16.2%-13.6 .3 13.3-3.7 .2 2.6-4.9 .2 4.6

57 2 37 9630.3 6.1 59.5 96.0

59.4% 2.1% 38.5% 100.0%

67.9% 11.8% 22.4% 36.1%

21.4% .8% 13.9% 36.1%26.7 -4.1 -22.54.8 -1.7 -2.97.3 -2.2 -5.919 7 73 99

31.3 6.3 61.4 99.019.2% 7.1% 73.7% 100.0%

22.6% 41.2% 44.2% 37.2%

7.1% 2.6% 27.4% 37.2%-12.3 .7 11.6-2.2 .3 1.5-3.3 .3 3.0

0 1 0 1.3 .1 .6 1.0

.0% 100.0% .0% 100.0%

.0% 5.9% .0% .4%

.0% .4% .0% .4%-.3 .9 -.6-.6 3.7 -.8-.7 3.8 -1.384 17 165 266

84.0 17.0 165.0 266.031.6% 6.4% 62.0% 100.0%

100.0% 100.0% 100.0% 100.0%

31.6% 6.4% 62.0% 100.0%

CountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likemy countries' languagefor foreigners% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I would like my countries' languagefor foreigners

Total

Chi-Square Tests

80.003a 8 .00080.856 8 .000

.026 1 .873

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

5 cells (33.3%) have expected count less than 5. The minimumexpected count is .06.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.220 .056 3.578 .000

.228 .046 4.523 .000

.208 .086 2.174 .030

.102 .024 .000c

.190 .038 .000c

.143 .025 5.626 .000d

.118 .020 5.626 .000d

.182 .032 5.626 .000d

-.028 .051 -.550 .582-.033 .060 -.550 .582

-.024 .044 -.550 .582

.036

.475

SymmetricCountry DependentI would like mycountries' language forforeigners DependentCountry DependentI would like mycountries' language forforeigners DependentSymmetricCountry DependentI would like mycountries' language forforeigners DependentSymmetricCountry DependentI would like mycountries' language forforeigners DependentCountry DependentI would like mycountries' language forforeigners Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.548 .000

.388 .000

.481 .000-.028 .052 -.550 .582-.025 .046 -.550 .582-.045 .081 -.550 .582

-.031 .058 -.502 .616c

.010 .054 .160 .873c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I would like my coun

Yes

No

Country * I would like gymnastics lessons

Crosstab

9 3 15 277.5 5.2 14.3 27.0

33.3% 11.1% 55.6% 100.0%

12.2% 5.9% 10.6% 10.2%

3.4% 1.1% 5.6% 10.2%1.5 -2.2 .7.5 -1.0 .2.7 -1.1 .30 7 36 43

12.0 8.2 22.8 43.0.0% 16.3% 83.7% 100.0%

.0% 13.7% 25.5% 16.2%

.0% 2.6% 13.5% 16.2%-12.0 -1.2 13.2-3.5 -.4 2.8-4.4 -.5 4.4

54 7 35 9626.7 18.4 50.9 96.0

56.3% 7.3% 36.5% 100.0%

73.0% 13.7% 24.8% 36.1%

20.3% 2.6% 13.2% 36.1%27.3 -11.4 -15.95.3 -2.7 -2.27.8 -3.7 -4.111 33 55 99

27.5 19.0 52.5 99.011.1% 33.3% 55.6% 100.0%

14.9% 64.7% 39.0% 37.2%

4.1% 12.4% 20.7% 37.2%-16.5 14.0 2.5-3.2 3.2 .3-4.7 4.5 .6

0 1 0 1.3 .2 .5 1.0

.0% 100.0% .0% 100.0%

.0% 2.0% .0% .4%

.0% .4% .0% .4%-.3 .8 -.5-.5 1.8 -.7-.6 2.1 -1.174 51 141 266

74.0 51.0 141.0 266.027.8% 19.2% 53.0% 100.0%

100.0% 100.0% 100.0% 100.0%

27.8% 19.2% 53.0% 100.0%

CountExpected Count% within Country% within I would likegymnastics lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likegymnastics lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likegymnastics lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likegymnastics lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likegymnastics lessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likegymnastics lessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes NoI would like gymnastics lessons

Total

Chi-Square Tests

85.592a 8 .00093.091 8 .000

.168 1 .682

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .19.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.216 .050 4.000 .000

.257 .042 5.644 .000

.160 .070 2.126 .034

.137 .027 .000c

.157 .030 .000c

.153 .025 5.950 .000d

.136 .023 5.950 .000d

.173 .028 5.950 .000d

.004 .050 .079 .937

.004 .054 .079 .937

.004 .047 .079 .937

.208

.485

SymmetricCountry DependentI would like gymnasticslessons DependentCountry DependentI would like gymnasticslessons DependentSymmetricCountry DependentI would like gymnasticslessons DependentSymmetricCountry DependentI would like gymnasticslessons DependentCountry DependentI would like gymnasticslessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.567 .000

.401 .000

.493 .000

.004 .050 .079 .937

.004 .049 .079 .937

.006 .074 .079 .937

.013 .059 .215 .830c

-.025 .055 -.409 .683c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

I would like gymnast

Yes

No

Country * I would like fashion-embroidery lessons

Crosstab

8 4 15 277.3 4.3 15.4 27.0

29.6% 14.8% 55.6% 100.0%

11.1% 9.5% 9.9% 10.2%

3.0% 1.5% 5.6% 10.2%.7 -.3 -.4.3 -.1 -.1.3 -.1 -.20 9 34 43

11.6 6.8 24.6 43.0.0% 20.9% 79.1% 100.0%

.0% 21.4% 22.4% 16.2%

.0% 3.4% 12.8% 16.2%-11.6 2.2 9.4-3.4 .8 1.9-4.4 1.0 3.2

50 16 30 9626.0 15.2 54.9 96.0

52.1% 16.7% 31.3% 100.0%

69.4% 38.1% 19.7% 36.1%

18.8% 6.0% 11.3% 36.1%24.0 .8 -24.94.7 .2 -3.46.9 .3 -6.414 13 72 99

26.8 15.6 56.6 99.014.1% 13.1% 72.7% 100.0%

19.4% 31.0% 47.4% 37.2%

5.3% 4.9% 27.1% 37.2%-12.8 -2.6 15.4-2.5 -.7 2.1-3.7 -.9 4.0

0 0 1 1.3 .2 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .4-.5 -.4 .6-.6 -.4 .972 42 152 266

72.0 42.0 152.0 266.027.1% 15.8% 57.1% 100.0%

100.0% 100.0% 100.0% 100.0%

27.1% 15.8% 57.1% 100.0%

CountExpected Count% within Country% within I would likefashion-embroiderylessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likefashion-embroiderylessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likefashion-embroiderylessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likefashion-embroiderylessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likefashion-embroiderylessons% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I would likefashion-embroiderylessons% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I would like fashion-embroiderylessons

Total

Chi-Square Tests

61.087a 8 .00071.094 8 .000

.383 1 .536

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .16.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.210 .053 3.660 .000

.234 .051 4.174 .000

.175 .071 2.257 .024

.101 .024 .000c

.145 .033 .000c

.119 .022 5.428 .000d

.104 .019 5.428 .000d

.138 .025 5.428 .000d

-.081 .052 -1.552 .121-.089 .057 -1.552 .121

-.074 .048 -1.552 .121

.064

.472

SymmetricCountry DependentI would likefashion-embroiderylessons DependentCountry DependentI would likefashion-embroiderylessons DependentSymmetricCountry DependentI would likefashion-embroiderylessons DependentSymmetricCountry DependentI would likefashion-embroiderylessons DependentCountry DependentI would likefashion-embroiderylessons Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.479 .000

.339 .000

.432 .000-.081 .052 -1.552 .121-.077 .050 -1.552 .121-.121 .078 -1.552 .121

-.094 .060 -1.537 .126c

-.038 .055 -.618 .537c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

80

60

40

20

0

I would like fashion

Yes

No

Country * I would like discussion on a variety of topics

Crosstab

9 5 13 274.6 14.0 8.4 27.0

33.3% 18.5% 48.1% 100.0%

20.0% 3.6% 15.7% 10.2%

3.4% 1.9% 4.9% 10.2%4.4 -9.0 4.62.1 -2.4 1.62.4 -3.7 2.0

0 27 16 437.3 22.3 13.4 43.0

.0% 62.8% 37.2% 100.0%

.0% 19.6% 19.3% 16.2%

.0% 10.2% 6.0% 16.2%-7.3 4.7 2.6-2.7 1.0 .7-3.2 1.6 .9

27 56 13 9616.2 49.8 30.0 96.0

28.1% 58.3% 13.5% 100.0%

60.0% 40.6% 15.7% 36.1%

10.2% 21.1% 4.9% 36.1%10.8 6.2 -17.02.7 .9 -3.13.7 1.6 -4.7

9 50 40 9916.7 51.4 30.9 99.0

9.1% 50.5% 40.4% 100.0%

20.0% 36.2% 48.2% 37.2%

3.4% 18.8% 15.0% 37.2%-7.7 -1.4 9.1-1.9 -.2 1.6-2.6 -.3 2.5

0 0 1 1.2 .5 .3 1.0

.0% .0% 100.0% 100.0%

.0% .0% 1.2% .4%

.0% .0% .4% .4%-.2 -.5 .7-.4 -.7 1.2-.5 -1.0 1.545 138 83 266

45.0 138.0 83.0 266.016.9% 51.9% 31.2% 100.0%

100.0% 100.0% 100.0% 100.0%

16.9% 51.9% 31.2% 100.0%

CountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within I wouldlike discussion ona variety of topics% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

I would like discussion on a varietyof topics

Total

Chi-Square Tests

47.343a 8 .00057.141 8 .000

1.686 1 .194

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .17.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.112 .040 2.634 .008

.144 .066 2.030 .042

.070 .033 2.081 .037

.061 .016 .000c

.082 .018 .000c

.094 .019 4.854 .000d

.084 .017 4.854 .000d

.107 .021 4.854 .000d

-.068 .059 -1.154 .248-.073 .063 -1.154 .248

-.063 .055 -1.154 .248

.108

.336

SymmetricCountry DependentI would like discussionon a variety of topicsDependentCountry DependentI would like discussionon a variety of topicsDependentSymmetricCountry DependentI would like discussionon a variety of topicsDependentSymmetricCountry DependentI would like discussionon a variety of topicsDependentCountry DependentI would like discussionon a variety of topicsDependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.422 .000

.298 .000

.389 .000-.068 .059 -1.154 .248-.066 .057 -1.154 .248-.101 .088 -1.154 .248

-.077 .066 -1.259 .209c

-.080 .064 -1.300 .195c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

I would like discuss

Yes

No

Country * To participate in a team to publish a book with traditional recipes

Crosstab

9 3 15 276.6 6.4 14.0 27.0

33.3% 11.1% 55.6% 100.0%

13.8% 4.8% 10.9% 10.2%

3.4% 1.1% 5.6% 10.2%2.4 -3.4 1.0.9 -1.3 .3

1.1 -1.6 .40 16 27 43

10.5 10.2 22.3 43.0.0% 37.2% 62.8% 100.0%

.0% 25.4% 19.6% 16.2%

.0% 6.0% 10.2% 16.2%-10.5 5.8 4.7-3.2 1.8 1.0-4.1 2.3 1.6

46 12 38 9623.5 22.7 49.8 96.0

47.9% 12.5% 39.6% 100.0%

70.8% 19.0% 27.5% 36.1%

17.3% 4.5% 14.3% 36.1%22.5 -10.7 -11.84.7 -2.3 -1.76.7 -3.2 -3.010 32 57 99

24.2 23.4 51.4 99.010.1% 32.3% 57.6% 100.0%

15.4% 50.8% 41.3% 37.2%

3.8% 12.0% 21.4% 37.2%-14.2 8.6 5.6-2.9 1.8 .8-4.2 2.6 1.4

0 0 1 1.2 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.2 -.2 .5-.5 -.5 .7-.6 -.6 1.065 63 138 266

65.0 63.0 138.0 266.024.4% 23.7% 51.9% 100.0%

100.0% 100.0% 100.0% 100.0%

24.4% 23.7% 51.9% 100.0%

CountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional recipes% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

To participate in a team to publish abook with traditional recipes

Total

Chi-Square Tests

60.082a 8 .00069.343 8 .000

1.059 1 .303

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .24.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.149 .048 2.935 .003

.216 .040 5.035 .000

.063 .069 .874 .382

.096 .022 .000c

.097 .022 .000c

.113 .021 5.295 .000d

.102 .019 5.295 .000d

.127 .023 5.295 .000d

-.052 .050 -1.042 .297-.056 .053 -1.042 .297

-.049 .047 -1.042 .297

.100

.415

SymmetricCountry DependentTo participate in ateam to publish abook with traditionalrecipes DependentCountry DependentTo participate in ateam to publish abook with traditionalrecipes DependentSymmetricCountry DependentTo participate in ateam to publish abook with traditionalrecipes DependentSymmetricCountry DependentTo participate in ateam to publish abook with traditionalrecipes DependentCountry DependentTo participate in ateam to publish abook with traditionalrecipes Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.475 .000

.336 .000

.429 .000-.052 .050 -1.042 .297-.051 .049 -1.042 .297-.077 .074 -1.042 .297

-.059 .059 -.954 .341c

-.063 .056 -1.029 .304c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

To participate in a

Yes

No

Country * To participate in a team to publish a book with traditional myths and stories

Crosstab

9 4 14 277.6 4.3 15.1 27.0

33.3% 14.8% 51.9% 100.0%

12.0% 9.5% 9.4% 10.2%

3.4% 1.5% 5.3% 10.2%1.4 -.3 -1.1.5 -.1 -.3.6 -.1 -.50 10 33 43

12.1 6.8 24.1 43.0.0% 23.3% 76.7% 100.0%

.0% 23.8% 22.1% 16.2%

.0% 3.8% 12.4% 16.2%-12.1 3.2 8.9-3.5 1.2 1.8-4.5 1.5 3.0

55 6 35 9627.1 15.2 53.8 96.0

57.3% 6.3% 36.5% 100.0%

73.3% 14.3% 23.5% 36.1%

20.7% 2.3% 13.2% 36.1%27.9 -9.2 -18.85.4 -2.4 -2.67.9 -3.2 -4.811 22 66 99

27.9 15.6 55.5 99.011.1% 22.2% 66.7% 100.0%

14.7% 52.4% 44.3% 37.2%

4.1% 8.3% 24.8% 37.2%-16.9 6.4 10.5-3.2 1.6 1.4-4.8 2.2 2.7

0 0 1 1.3 .2 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .4-.5 -.4 .6-.6 -.4 .975 42 149 266

75.0 42.0 149.0 266.028.2% 15.8% 56.0% 100.0%

100.0% 100.0% 100.0% 100.0%

28.2% 15.8% 56.0% 100.0%

CountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with traditionalmyths and stories% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

To participate in a team to publish abook with traditional myths and

storiesTotal

Chi-Square Tests

73.839a 8 .00084.361 8 .000

1.105 1 .293

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .16.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.225 .051 4.043 .000

.263 .042 5.742 .000

.171 .074 2.126 .034

.125 .026 .000c

.149 .031 .000c

.141 .024 5.842 .000d

.124 .021 5.842 .000d

.163 .027 5.842 .000d

-.077 .050 -1.550 .121-.085 .055 -1.550 .121

-.071 .046 -1.550 .121

.072

.497

SymmetricCountry DependentTo participate in a teamto publish a book withtraditional myths andstories DependentCountry DependentTo participate in a teamto publish a book withtraditional myths andstories DependentSymmetricCountry DependentTo participate in a teamto publish a book withtraditional myths andstories DependentSymmetricCountry DependentTo participate in a teamto publish a book withtraditional myths andstories DependentCountry DependentTo participate in a teamto publish a book withtraditional myths andstories Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.527 .000

.373 .000

.466 .000-.078 .050 -1.550 .121-.074 .048 -1.550 .121-.115 .074 -1.550 .121

-.086 .058 -1.408 .160c

-.065 .055 -1.051 .294c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

To participate in a

Yes

No

Country * To participate in a team to publish a book with old pictures from our city or town

Crosstab

8 6 13 277.1 6.2 13.7 27.0

29.6% 22.2% 48.1% 100.0%

11.4% 9.8% 9.6% 10.2%

3.0% 2.3% 4.9% 10.2%.9 -.2 -.7.3 -.1 -.2.4 -.1 -.30 9 34 43

11.3 9.9 21.8 43.0.0% 20.9% 79.1% 100.0%

.0% 14.8% 25.2% 16.2%

.0% 3.4% 12.8% 16.2%-11.3 -.9 12.2-3.4 -.3 2.6-4.3 -.3 4.1

51 15 30 9625.3 22.0 48.7 96.0

53.1% 15.6% 31.3% 100.0%

72.9% 24.6% 22.2% 36.1%

19.2% 5.6% 11.3% 36.1%25.7 -7.0 -18.75.1 -1.5 -2.77.5 -2.1 -4.811 31 57 99

26.1 22.7 50.2 99.011.1% 31.3% 57.6% 100.0%

15.7% 50.8% 42.2% 37.2%

4.1% 11.7% 21.4% 37.2%-15.1 8.3 6.8-2.9 1.7 1.0-4.3 2.5 1.7

0 0 1 1.3 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.2 .5-.5 -.5 .7-.6 -.5 1.070 61 135 266

70.0 61.0 135.0 266.026.3% 22.9% 50.8% 100.0%

100.0% 100.0% 100.0% 100.0%

26.3% 22.9% 50.8% 100.0%

CountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish abook with old picturesfrom our city or town% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

To participate in a team to publish abook with old pictures from our city

or townTotal

Chi-Square Tests

67.597a 8 .00075.785 8 .000

.321 1 .571

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .23.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.205 .047 4.013 .000

.240 .041 5.346 .000

.160 .063 2.358 .018

.111 .025 .000c

.129 .028 .000c

.123 .022 5.441 .000d

.111 .020 5.441 .000d

.138 .025 5.441 .000d

-.036 .051 -.714 .475-.038 .054 -.714 .475

-.034 .048 -.714 .475

.087

.485

SymmetricCountry DependentTo participate in a teamto publish a book withold pictures from ourcity or town DependentCountry DependentTo participate in a teamto publish a book withold pictures from ourcity or town DependentSymmetricCountry DependentTo participate in a teamto publish a book withold pictures from ourcity or town DependentSymmetricCountry DependentTo participate in a teamto publish a book withold pictures from ourcity or town DependentCountry DependentTo participate in a teamto publish a book withold pictures from ourcity or town Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.504 .000

.356 .000

.450 .000-.036 .051 -.714 .475-.036 .050 -.714 .475-.053 .074 -.714 .475

-.036 .060 -.588 .557c

-.035 .055 -.566 .572c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

60

50

40

30

20

10

0

To participate in a

Yes

No

Country * To participate in a team to publish a tourist guide about our city or town

Crosstab

9 6 12 277.9 4.0 15.1 27.0

33.3% 22.2% 44.4% 100.0%

11.5% 15.4% 8.1% 10.2%

3.4% 2.3% 4.5% 10.2%1.1 2.0 -3.1.4 1.0 -.8.5 1.2 -1.30 8 35 43

12.6 6.3 24.1 43.0.0% 18.6% 81.4% 100.0%

.0% 20.5% 23.5% 16.2%

.0% 3.0% 13.2% 16.2%-12.6 1.7 10.9-3.6 .7 2.2-4.6 .8 3.7

56 1 39 9628.2 14.1 53.8 96.0

58.3% 1.0% 40.6% 100.0%

71.8% 2.6% 26.2% 36.1%

21.1% .4% 14.7% 36.1%27.8 -13.1 -14.85.2 -3.5 -2.07.8 -4.7 -3.813 24 62 99

29.0 14.5 55.5 99.013.1% 24.2% 62.6% 100.0%

16.7% 61.5% 41.6% 37.2%

4.9% 9.0% 23.3% 37.2%-16.0 9.5 6.5-3.0 2.5 .9-4.5 3.4 1.7

0 0 1 1.3 .1 .6 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.3 -.1 .4-.5 -.4 .6-.6 -.4 .978 39 149 266

78.0 39.0 149.0 266.029.3% 14.7% 56.0% 100.0%

100.0% 100.0% 100.0% 100.0%

29.3% 14.7% 56.0% 100.0%

CountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participatein a team to publish atourist guide about ourcity or town% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

To participate in a team to publish atourist guide about our city or town

Total

Chi-Square Tests

80.221a 8 .00096.644 8 .000

.574 1 .449

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

4 cells (26.7%) have expected count less than 5. The minimumexpected count is .15.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.211 .053 3.704 .000

.257 .043 5.459 .000

.145 .077 1.754 .079

.134 .025 .000c

.152 .030 .000c

.162 .023 6.736 .000d

.142 .021 6.736 .000d

.188 .027 6.736 .000d

-.053 .049 -1.094 .274-.059 .054 -1.094 .274

-.049 .045 -1.094 .274

.057

.479

SymmetricCountry DependentTo participate in a teamto publish a touristguide about our city ortown DependentCountry DependentTo participate in a teamto publish a touristguide about our city ortown DependentSymmetricCountry DependentTo participate in a teamto publish a touristguide about our city ortown DependentSymmetricCountry DependentTo participate in a teamto publish a touristguide about our city ortown DependentCountry DependentTo participate in a teamto publish a touristguide about our city ortown Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.549 .000

.388 .000

.481 .000-.054 .049 -1.094 .274-.051 .047 -1.094 .274-.080 .073 -1.094 .274

-.056 .058 -.919 .359c

-.047 .054 -.757 .450c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

To participate in a

Yes

No

Country * To participate in a team to publish a book with traditional songs

Crosstab

9 4 14 276.7 5.7 14.6 27.0

33.3% 14.8% 51.9% 100.0%

13.6% 7.1% 9.7% 10.2%

3.4% 1.5% 5.3% 10.2%2.3 -1.7 -.6.9 -.7 -.2

1.1 -.8 -.30 4 39 43

10.7 9.1 23.3 43.0.0% 9.3% 90.7% 100.0%

.0% 7.1% 27.1% 16.2%

.0% 1.5% 14.7% 16.2%-10.7 -5.1 15.7-3.3 -1.7 3.3-4.1 -2.1 5.3

43 21 32 9623.8 20.2 52.0 96.0

44.8% 21.9% 33.3% 100.0%

65.2% 37.5% 22.2% 36.1%

16.2% 7.9% 12.0% 36.1%19.2 .8 -20.03.9 .2 -2.85.7 .2 -5.114 27 58 99

24.6 20.8 53.6 99.014.1% 27.3% 58.6% 100.0%

21.2% 48.2% 40.3% 37.2%

5.3% 10.2% 21.8% 37.2%-10.6 6.2 4.4-2.1 1.3 .6-3.1 1.9 1.1

0 0 1 1.2 .2 .5 1.0

.0% .0% 100.0% 100.0%

.0% .0% .7% .4%

.0% .0% .4% .4%-.2 -.2 .5-.5 -.5 .6-.6 -.5 .966 56 144 266

66.0 56.0 144.0 266.024.8% 21.1% 54.1% 100.0%

100.0% 100.0% 100.0% 100.0%

24.8% 21.1% 54.1% 100.0%

CountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of TotalResidualStd. ResidualAdjusted ResidualCountExpected Count% within Country% within To participate ina team to publish a bookwith traditional songs% of Total

Wales

Romania

Lithuania

Cyprus

.00

Country

Total

Missing Yes No

To participate in a team to publish abook with traditional songs

Total

Chi-Square Tests

56.144a 8 .00065.016 8 .000

.048 1 .826

.b

266

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationMcNemar TestN of Valid Cases

Value dfAsymp. Sig.

(2-sided)Exact Sig.(2-sided)

3 cells (20.0%) have expected count less than 5. The minimumexpected count is .21.

a.

Computed only for a PxP table, where P must be greater than 1.b.

Directional Measures

.138 .048 2.747 .006

.174 .041 3.952 .000

.090 .068 1.274 .203

.081 .021 .000c

.121 .025 .000c

.107 .020 5.145 .000d

.095 .018 5.145 .000d

.121 .023 5.145 .000d

.008 .053 .151 .880

.009 .057 .151 .880

.007 .049 .151 .880

.134

.427

SymmetricCountry DependentTo participate in ateam to publish abook with traditionalsongs DependentCountry DependentTo participate in ateam to publish abook with traditionalsongs DependentSymmetricCountry DependentTo participate in ateam to publish abook with traditionalsongs DependentSymmetricCountry DependentTo participate in ateam to publish abook with traditionalsongs DependentCountry DependentTo participate in ateam to publish abook with traditionalsongs Dependent

Lambda

Goodman andKruskal tau

Uncertainty Coefficient

Nominal byNominal

Somers' dOrdinal by Ordinal

EtaNominal by Interval

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on chi-square approximationc.

Likelihood ratio chi-square probability.d.

Symmetric Measures

.459 .000

.325 .000

.417 .000

.008 .053 .151 .880

.008 .051 .151 .880

.012 .080 .151 .880

.014 .061 .225 .822c

-.014 .058 -.220 .826c

.d

266

PhiCramer's VContingency Coefficient

Nominal by Nominal

Kendall's tau-bKendall's tau-cGammaSpearman Correlation

Ordinal by Ordinal

Pearson's RInterval by IntervalKappaMeasure of Agreement

N of Valid Cases

ValueAsymp.

Std. Errora Approx. Tb Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Based on normal approximation.c.

Kappa statistics cannot be computed.They require a symmetric 2-way table in which the valuesof the first variable match the values of the second variable.

d.

Risk Estimate

aOdds Ratio forCountry (.00 / Cyprus)

Value

Risk Estimate statistics cannot be computed. Theyare only computed for a 2*2 table without empty cells.

a.

Country

WalesRomaniaLithuaniaCyprus

Cou

nt

70

60

50

40

30

20

10

0

To participate in a

Yes

No