contigency table excercise -- spss

8/10/2019 Contigency Table Excercise -- SPSS

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Contingency Table Exercise Iram Nisa

Introduction

In order to study the contingency table, the research is conducted to find out the

relationship between the two variables geographical location and political affiliation

among voters in Pakistan !or this purpose, we have under took the study of two

variables "awalpindi and Non#"awalpindi residents in geographical location and three

variables PPPP , P$%N, &I in political affiliation 'e have conducted research to find

out the strength of association between the geographical location and political affiliation

we have taken the two variables ()eographical %ocation* and (political affiliation, then

taking the sample of students of ++#- from !atima &innah 'omen .niversity

"awalpindi the geographical location is sub#divided into "awalpindi and non#

"awalpindi residents while political affiliation into three parties as Pakistan People/s

Party Parliamentarians 0PPPP1, Pakistan $uslim %eague Nawa2 0P$%N1 and &amat#e#

Islami 0&I1

b- Objective

3To ascertain the relationship between geographical location and political affiliation4

c- Variables

'e will consider the two categorical variables

i- Geographical Location: %iteral meaning of geographical location is the exact

location of one ob5ect relative to another or in a general area, whereas the contextual

meaning is where the students of class reside

6




)eographical location is further categori2ed into7

• "esidents of "awalpindi

• "esidents of non#"awalpidi

ii- Political Affiliation: %iteral meaning of Political ffiliation to accept as a member of

)roup of persons organi2ed to ac8uire and exercise political power, whereas the

contextual meaning is student*s votes are affiliated with which political party

Political ffiliation is further categori2ed into7

• Pakistan People/s Party Parliamentarians 0PPPP1

• Pakistan $uslim %eague Nawa2 0P$%N1

• &amat#e#Islami 0&I1

d- Scales of Measureent

+oth the variables )eographical %ocation and Political ffiliation are 8ualitative in

nature 'e will use (Nominal scale of measurement* to study the relationship between

these variables

e- Statistical !ool

table (lan +ryman 9 Emma +ell on "esearch $ethodology* annexed at page#:

suggest that when we a nominal variable versus a nominal variable then we use

• Contigency Table

• Chi#s8uare χ ;

<

http://en.wikipedia.org/wiki/Chi_(letter)





• Cramer*s -

=tatistical Tools for >ifferent =cales

"oinal Ordinal Interval#

$atio

%ichoto&

"oinal

Contingency

table?@@

Chi s8uare χ ;Cramer*s#-

Contingency

table


Contingency

table


0If the IA"

variable can be

identified as the

dependentvariable compare

mean and eta

0nova11

Contingency

table


Ordinal Contingency

table


=pearmen*s "ho

0@1

=pearmen*s

"ho 0@1

=pearmen*s "ho

0@1

Interval#

$atio

Contingency

tableChi s8uare χ ;

Cramer*s#-

=pearmen*s "ho

or nova

Pearson*s "ho

0Correlation1

=pearmen*s "ho

0@1

%ichoto&

Contingency

table


=pearmen*s "ho

0@1

=pearmen*s

"ho 0@1

Phi# Co#efficient

0?1

0Table7 661

f- %ata 'ollection

'e had considered the population of Pakistan to determine the dependence of political

affiliation on geographical location In order to deduce the results, we chose the sample

of <B students of ++#- from !atima &innah 'omen .niversity "awalpindi belonging

to different areas of Pakistan "elative 8uestions were asked about their affiliation with

:


















different political parties 0ie PPPP, P$%N and &I1 and the geographical location 0ie

"awalpindi, non#"awalpindi1 fter that we have assembled the collected data from the

sample

g- %ata anal&sis

'e have analy2ed the data obtained from the sample using =P== version 6:

utput is given on page D 6<, 6:

h- %ata (ntr&:

'e will use the =P== version#6: to analy2e the data 8uickly we will go into the =P== for

following the following path

• Pop up box will open ask for the type of file you want to open

• ere you will select the (Create new 8uery using database wi2ard* then press ok

• New database sheet will be opened

=tart ll programs =P== 6:F

for windows6:

=P== for

windows

G




0Table7 6<1

There are two sheets appeared in =P== window on the down#left corner

• -ariable -iew

• >ata -iew

Variable Vie):

• !irstly, we will enter the data into the sheet of variable view

• Click the (variable view* written on the left Dbottom of the window

• (-ariable view* sheet will be displayed

B




0Table7 6<1

Now enter the values in the columns given in the variable view

• Name: Enter the name of the variable ()eoloc*

• Type7 =elect the type of data (numeric*

• %abel7 'rite the full name of the variable as ()eographical %ocation*

• -alues7

o Click the right button appeared in the column

o Pop#up +ox will be opened

o Enter values in the boxes as given the table

H




0Table7 6:1

• $easure7 Enter the scale of measurement of the respective variable ie Nominal

%ata Vie)

• !irst of all, click the (>ata view* written on the left bottom corner of the window

• >ata view sheet will be open

• Enter the data of geographical location and political affiliation in the columns

under their respective headings




0Table7 6G1

i- $esults and Output

'ontingenc& !able7

The following process is carried to form the contingency table

•

Click#left on the (analy2e* in the $enu# +ar, scroll will appear

• Click on the descriptive statistics, new scroll bar will appear then click the cross

tabs

J




0Table7 6B1

Pop#up box named (Crosstabs* will appear as given in table, move variable )eographical

%ocation in the ("ow box* and move variable Political ffiliation in the (Column box*

0Table7 6H1

K




<nd =tep7 Click box along the (display clustered bar charts*

Click the button (Cells*

nother Pop#up box named (Crosstabs7 Cell >isplay* will open

:rd =tep7 click the row under the heading (Percentage*, press (Continue* then L

0Table7 61

6F




)raphs M%ine M$ultiple M >efine M Category axis M ok

In the $enu +ar, go to graphs then click the (%ine* in the scroll bar

0Table7 6J1

• Pop#up +ox will appear named as (%ine Chart* then

6st =tep7 click the ($ultiple*

<nd =tep7 click >efine button 0as in table7 1

0Table7 6K1

66




• $ove )eographical %ocation into the Category x#xis then click L

0Table7 66F1

6<




Output:

Geographical Location * Political Affiliation 'rosstabulation

6 G 6 H

6HI HHI 6HI 6FFF

: 6: : 6K

6BJ HJG 6BJ 6FFF

G 6I G <B

6HF HJF 6HF 6FFF

Count

within )eographical

%ocation

Count

within )eographical

%ocation

Count

within )eographical

%ocation

"wp

NA"wp

)eographical

%ocation

Total

P N &

Political ,ffiliation

Total

N/RwpRwp

Geographical Location

14

12

10

8

6

4

2

0

C o u n t

J

N

P

Political Affiliation

Bar Chart

6:




0Table7 6661

j- Anal&sis:

!or this purpose, we have under took the study of two variables "awalpindi and Non#

"awalpindi residents in geographical location and three variables PPPP , P$%N, &I in

political affiliation 'e have conducted research to find out the strength of association

between the geographical location and political affiliation 'e took the sample of <B girls

from !atima &innah 'omen .niversity "awalpindi fter analysis, we found the

following results 0as shown in table7 6661

6 "awalpindi

a PPPP has 6HH voters

b P$%N has HHH voters

c &I has 6HH voters

< Non# "awalpindi

a PPPP has 6BJ voters

b P$%N has HJG< voters

c &I has 6BJ voters

: verall "esult

a PPPP has 6H voters

b P$%N has HJ voters

c &I has 6H voters

6G




Insight

'e will find out the relationship between geographical %ocation and Political affiliation

from the line diagram 0shown in table 66<1 +y keeping in view the line diagram we see

that though the %ines do not intersect but still they are parallel which leads to the

conclusion that there is a very weak interaction between geographical location and

political affiliation In statistical parlance we say that the two variables under study are

weekly associated ie to the change in geographical location, the voting patterns changes

but a little

Graph

N/RwpRwp

Geographical Location

14

12

10

8

6

4

2

0

C

o u n t

J

N

P

Political Affiliation

0Table7 66<1

6B




+- (,planation:

• 'hen the lines are parallel to each other then there is not relationship between the

variable

• 'hen the lines intersect each other then there is strong relationship between the

variable

• 'hen the lines are neither parallel nor intersect, will meet at a point then there is

a week relationship between them

• 'hen there is increase in one variable and decrease in other than there always is a

strong interaction

6H




$ear+s

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