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Crosstabs

How do we assess the relationship between two variables?(Well bring in more variables later.)

Various ways, espeially with interval!level data"

one o# the most ommon ways is with rosstabs.

$Crosstab% is a ontration o# $Cross &abulation%

'lso alled a ontingeny table

What is a (simple) rosstab?

' table based on two variables, where the ell entries are the ounts or perentages o# ases that #all in that row or olumn ategory. o, also alled a bivariate #reueny table.

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W'*++-

&heres going to be a lot oming at you (in

lass). t reuires paying attention, thin/ing

(wow0).

1ut2it only involves perentages, so noompliated $statistis% (yet).

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'n e3ample gender 4 tv wathing

We begin with the

observations (persons).

' #ile o# about a thousand

people would have data li/e

this (e3ept that -ender andWathing &V would be oded

using numbers).

5ou would reate the ross!tab

(presumably using 62

these are real bears to do byhand).

7bserva!tionnumber

-ender

Wath(some &Vprogram)

8 9 +

: 9 5; 9 +

< = +

> = 5

9 5@ @ @

8AA< 9 5

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're Women =ore Bi/ely to Wath &han =en?

5ou might want to as/ the

uestion are women more

li/ely to wath this partiular tv

program than men are?

o, you display the data in a

rosstab (in this ase a :3:

table).

1ut how do you read it?

9emale =ale

Wath ;;8 8A

DWath :8A :E;

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'lmost without e3eption, you want to loo/

at perentages rather than numbers o#

ases.

1ut, whih way to perentage?

'dd to 8AAF within ategories o# the iv.

n the way that ma/es sense #or theuestion at hand. (*euires thin/ing.)

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We an F either way

(by rows) (by olumns)9 = &otal

W ;;8

(8F)

8A

(;F)

>A8

(>AF)

DW :8A

(;EF)

:E;

(;F)

>A;

(>AF)

&otal >

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+ote

ve perentaged the total row or ol.

+ot neessary, but o#ten use#ul, and its done automatially by 6.

ve used whole numbers. +othing

about reating tables de#ines auray level. ont overdo

auray.

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Whih way is orret?

*eall

v is the one were trying to e3plain. v is the one used to e3plain the dv.

&he uestion we are as/ing is are

women more li/ely to wath this partiular tv program than men are?

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1urning uestion

oes it ma/e any di##erene whihvariable ma/es up the rows, and whih theolumns?

+o. &heres no agreed!upon onvention#or whether the iv goes in the rows orolumns (te3t notwithstanding). BUT

# you swith row and olumn variables,then whih perentages are right (#or youruestion) will also hange.

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=ore analytial matters.

llustration o di##erent areers attrat

di##erent partisans? (lass survey)

're emorats or *epublians more li/ely to go into

Baw?

6olitis?

1usiness?

'ademia?

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6arty I Career

*eode? +ote small J o# ases in somerows. 'lso, are nd and 7ther di##erent?

Ks? elete or ombine with other rows?

Party ID * career Crosstabulation

: > 8 8.AF :>.AF 8AA.AF

: A : A A.AF .AF >A.AF .AF 8AA.AF

:: 8 8< >E

;.;F :G.GF :;.F 8A.:F 8AA.AF

Count

F within 6arty

Count

F within 6arty

Count

F within 6arty

Count

F within 6arty

Count

F within 6arty

Count

F within 6arty

*epublian

emorat

ndependent

7ther

onLt Know

6arty

&otal

law politis business aademiMedu

areer

&otal

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=ore analytial matters (ont.)

&hese are analytial matters.

ont ma/e meaningless ombinations

Nust beause o# small +s. Keep inMdelete $dont /nows% depending

on your reasoning about them.

uppose we deide to /eep Ks andombine the three smallest ategories.

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*eoded

&able is simpler, easier to read.

=ore meaning#ul beause it doesnt ma/e

distintions we arent really interested in.

Party ID * career Crosstabulation

? : > 8 8