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SAMPLING AND
ITS TYPES
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SAMPLING
Target Population or Universe
The population to which the investigator wants togeneralize his results
Sampling Unit:
smallest unit from which sample can be selected
Sampling frame
The sampling frame is the list from which the potentialrespondents are drawn Telephone director List of five star !otel List of student
Sampling sceme
Method of selecting sampling units from sampling frame
Sample" all selected respondent are sample
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SAMPL#
TA$G#T P%P&LATI%N
SAMPL# &NIT
SAMPL#
• A population can be defined as including all people or itemswith the characteristic one wishes to understand'
• (ecause there is ver rarel enough time or mone to gather
information from everone or everthing in a population) the
goal becomes finding a representative sample *or subset+ of
that population'
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SAMPLING ($#A,-%.N
All university in India
All university Haryana
List of Haryana university
Three university in haryana
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SAMPLING……
To whom do ou want to generalize our results0All 1ive Star !otel
All Travel Agenc
All !otel 2ustomer
.omen aged 34564 ears%ther
Sample size " Minimum size is 78 no'
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SAMPLING$$%
7 factors that influence sample representative5nessSampling procedureSample size
Participation *response+
.hen might ou sample the entire population0.hen our population is ver small
.hen ou have e9tensive resources.hen ou don/t e9pect a ver high response
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The sample must be"3' representative of the population:
;' appropriately sized *the larger the better+:
7' unbiased :
6' random *selections occur b chance+:
!at is Goo& Sample#
Merits of SamplingSize of population1und re
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T'E (ESP(ESENATI)N *ASIS P$%(A(ILIT= SAMPLING N%N P$%(A(ILIT= SAMPLING
ELEMENT SELE+TI)N TE+'NI,E
$#ST$I2T#- SAMPLING &N $#ST$I2T#- SAMPLING
TYPES )- SAMPLE *ASED )N T!) -A+T)(S:
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•Probability sample – a method of sampling thatuses of random selection so that all units/ cases inthe population have an equal probability of being
chosen.• Non-probability sample – does not involverandom selection and methods are not based onthe rationale of probability theory.
Types of Sampling
Sampling
Techniques
Probability Non-
Probability
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Probabilit *$andom+ Samples Simple random sample
Sstematic random sample
Stratified random sample
2luster sample
Probabilit
Sampling
Simple
$andom
Sampling
Sstematic
Sampling
Stratified
$andom
Sampling
Proportionate-is Proportionate
2luster
Sampling
%ne5
Stage
Two
Stage
Multi5
Stage
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Non5Probabilit Samples
2onvenience samples *ease of access+
sample is selected from elements of a population thatare easil accessible
Purposive sample *>udgmental Sampling+
=ou chose who ou thin? should be in the stud@uota Sampling
Snowball Sampling *friend of friend'etc'+
Non5
Probabilit
2onvenience
Sampling
@uota
Sampling
>udgment
Sampling
Snowball
Sampling
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Difference .et/een Pro.a.ilit"
sampling an& Non Pro.a.ilit"
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SIMPLE (AND)M SAMPLING• Applicable when population is small) homogeneous B
readil available• All subsets of the frame are given an e
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Simple random sampling
Ever" su.set of a specifie& si0e n from te population
as an e1ual cance of .eing selecte&
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Suita.ilit"
This method is suitable for small homogeneous $andoml selecting units from a sampling frame'
C$andom/ means mathematicall each unit from the
sampling frame has an e
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(EPLA+EMENT )- SELE+TED UNITS
Sampling schemes ma be without replacement or with
replacement
1or e9ample) if we catch fish) measure them) and
immediatel return them to the water before continuingwith the sample) this is a with replacement design)
because we might end up catching and measuring the
same fish more than once' !owever) if we do not return
the fish to the water *e'g' if we eat the fish+) this becomesa without replacement design'
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• Similar to simple random sample' No table of random
numbers D select directl from sampling frame' $atio
between sample size and population size
S"stematic Sampling
-efine population
-evelopsampling
frame
-ecide thesample size
.or? outwhat fractionof the framethe sample
sizerepresents
Selectaccording tofraction *388sample from
3)888 frame then38E so ever
38th unit+
1irst unitselect brandomnumbers
then evernth unitselected
*e'g' ever38th+
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AD2ANTAGES: Sample eas to select
Suitable sampling frame can be identified easil
Sample evenl spread over entire reference population 2ost effective
DISAD2ANTAGES:
Sample ma be biased if hidden periodicit in populationcoincides with that of selection'
#ach element does not get e
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Systematic sampling
#ver member * for e9ample" ever ;8th person+ is
selected from a list of all population members'
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Stratifie& (an&om Sample
The population is divided into two or more groupscalled strata) according to some criterion) such as
geographic location) grade level) age) or income) and
subsamples are randoml selected from each strata'
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Stratied RandomSample
e!nepopulation
evelopsampling
frameaccording to
characteristicsrequired
etermine theproportion of
eachpopulationvariable of
interest
Systematicsampling
methods canthen be follo$edto select sample
unit
Stratified random sampling can be classified in to
a% Proportionate stratifie& sampling
It involves drawing a sample from each stratum in
proportion to the letter/s share in total population
b' Disproportionate stratifie& sampling proportionate representation is not given to strata
it necesser involves giving over representation to
some strata and under representation to other'
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ST$ATI1I#- SAMPLINGA&vantage :
Enancement of representativeness to eac sample 'iger statistical efficienc" Eas" to carr" out
Disa&vantage:
+lassification error Time consuming an& e3pensive Prior 4no/le&ge of composition an& of
&istri.ution of population
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+LUSTE( SAMPLING 2luster sampling is an e9ample of Ftwo5stage samplingF '
1irst stage a sample of areas is chosen: Second stage a sample of respondents within those areas is
selected'
Population divided into clusters of homogeneous units) usuall
based on geographical contiguit' Sampling units are groups rather than individuals'
A sample of such clusters is then selected'
All units from the selected clusters are studied' The population is divided into subgroups *clusters+ li?e
families' A simple random sample is ta?en of the subgroups
and then all members of the cluster selected are surveed
%luster sampling
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%luster sampling
Section 4
Section 5
Section 3
Section 2Section 1
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2L&ST#$ SAMPLING'
Advantages "
2uts down on the cost of preparing a samplingframe' This can reduce travel and otheradministrative costs'
-isadvantages" sampling error is higher for a simple
random sample of same size' %ften used to evaluate
vaccination coverage in #PI
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• +luster sampling" selecting a sample based on specific) naturall occurring
groups *clusters+ within a population'
5 #9ample" randoml selecting ;8 hospitals from a list of all
hospitals in #ngland'
Multi5stage sampling" cluster sampling repeated at a number of levels' 5
#9ample" randoml selecting hospitals b count and then a sample of patientsfrom each selected hospital'
2omple9 form of cluster sampling in which two or more levels of units areembedded one in the other'
1irst stage) random number of districts chosen in all states'
1ollowed b random number of talu?as) villages' Then third stage units will be houses'
All ultimate units *houses) for instance+ selected at last step are surveed'
+luster6 multi5stage ran&om sample
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-ifference (etween Strata and 2lusters
Although strata and clusters are both non5overlappingsubsets of the population) the differ in several was'
All strata are represented in the sample: but onl asubset of clusters are in the sample'
.ith stratified sampling) the best surve results occurwhen elements within strata are internallhomogeneous' !owever) with cluster sampling) the
best results occur when elements within clusters areinternall heterogeneous
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Non Pro.a.ilit"
+)N2ENIEN+E SAMPLING
Sometimes ?nown as gra. or opportunit" sampling or acci&ental or apa0ar&
sampling% Selection of whichever individuals are easiest to reach
It is done at the convenienceH of the researcher 1or e9ample) if the interviewer was to conduct a surve at a
shopping center earl in the morning on a given da) the peoplethat heshe could interview would be limited to those given thereat that given time) which would not represent the views of othermembers of societ in such an area) if the surve was to beconducted at different times of da and several times per wee?'
This tpe of sampling is most useful for pilot testing' In social science research) snowball sampling is a similar
techni
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Adantage! A sample selected for ease of
access& immediately 'no$n population group andgood response rate.
"isadantage! cannot generalise !ndings (donot 'no$ $hat population group the sample is
representative of) so cannot move beyonddescribing the sample.
•*roblems of reliability
•o respondents represent thetarget population
•"esults are not generali#able
+onvenience Sampling
Sunil +umarUse results that are eas to et
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7u&gmental sampling or Purposive sampling 5 The researcher chooses the sample based on who
the thin? would be appropriate for the stud' This isused primaril when there is a limited number of
people that have e9pertise in the area being
researched
Selected based on an e9perienced individual/s belief Advantages
(ased on the e9perienced person/s Judgment
-isadvantages 2annot measure the respresentativeness of the
sample
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,U)TA SAMPLING
The population is first segmented into mutuall e9clusive sub5groups) Just as in stratified sampling'
Then Judgment used to select subJects or units from each segment based on a specified proportion'
1or e9ample) an interviewer ma be told to sample ;88 femalesand 788 males between the age of 64 and K8'
It is this second step which ma?es the techni
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,uota sampling
(ased on prespecified
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Sno/.all Sampling &seful when a population is hidden or difficult to gain access to' The
contact with an initial group is used to ma?e contact with others' $espondents identif additional people to included in the stud
The defined target mar?et is small and uni
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*otential Sources of ,rror in "esearch esigns
S#rrogate $nformation%rror
&eas#rement %rror
Pop#lation "enition
%rrorSampling 'rame %rror
Respondent Selection%rror
(#estioning %rror
Recording %rror
)*eating %rror
$nability %rror
+n,illingness%rror
Total %rror
Non-sampling%rror
RandomSampling
%rror
Non-response%rror
Response%rror
$nterie,er
%rror
Respondent
%rror
Researc*er
%rror
, i H it lit
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,rrors in Hospitality"esearch
The total error is the variation bet$een the true mean value in
the population of the variable of interest and the observed meanvalue obtained in the mar'eting research pro-ect.
Random sampling error is the variation bet$een the true meanvalue for the population and the true mean value for the originalsample.
Non-sampling errors can be attributed to sources other than
sampling& and they may be random or nonrandom includingerrors in problem de!nition& approach& scales& questionnairedesign& intervie$ing methods& and data preparation and analysis.on0sampling errors consist of non0response errors and responseerrors.
Non-response error arises $hen some of the respondents
included in the sample do not respond. Response error arises $hen respondents give inaccurate
ans$ers or their ans$ers are misrecorded or misanaly#ed
S li
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• The larger the sample si#e the more li'ely errorin the sample $ill decrease.
•1ut& beyond a certain point increasing samplesi#e does not provide large reductions in samplingerror.
•Accuracy is a re2ection of the sampling error and
con!dence level of the data.
Sampling %rrorand )ondence
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,rrors in Sampling
on03bservation ,rrors Sampling error naturally occurs
%overage error people sampled do not
match the population of interest 4nderrepresentation
on0response $on5t or can5t participate
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,rrors of 3bservation
Intervie$ error0 interaction bet$eenintervie$er and person being surveyed
"espondent error respondents have
di6cult time ans$ering the question 7easurement error inaccurate
responses $hen person doesn5tunderstand question or poorly $orded
question ,rrors in data collection
Sunil +umar
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Thank
You