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Chi-Square test in SPSS

Chi-Square test in SPSS

The Chi-Square test of independence is used to test whether there is an association among categorical variables. 

Assumptions:

  1. The Chi-Square test requires variables to be categorical (ordinal or nominal).

  2. Variables should have two or more categories.

Here, we have taken two categorical variables, namely, Anxiety and Body mass index. In Anxiety, we labelled 1 as ‘No’ and 2 as ‘Yes’, and in Body mass index, we labelled 1 as ‘normal’, 2 as ‘overweight’ and 3 as ‘obese’.

In SPSS, Chi-Square test is found in Analyze > Descriptive Statistics > Crosstabs

Then, we will get ‘Crosstabs’ dialog box.

We have to add one variable in ‘Row(s)’ box and one variable in ‘Column(s)’ box.

We have added Anxiety into ‘Row(s) box’ and Body mass index into ‘Column(s)’ box.

In the statistics dialog box, we have to add ‘Chi-square’. 

Click on ‘Continue’.

Then, in the cells dialog box, we have to add ‘Observed’ under the ‘Counts’ group and add ‘Row’ and ‘Column’ under the ‘Percentages’ group. Then, click on ‘Continue’ and ‘Ok’.

Output of Chi-Square Test

We will get a crosstabulation of Anxiety and Body mass index. We will get row-wise and column-wise percentages.

Here, 70.8% of 24 overweight people have anxiety.

Then, we will get a table of Chi-Square Tests. 

In this table, we would be interested in the results of the ‘Pearson Chi-Square’ row. Here, the p value is equal to 0.000, which is less than 0.05. Thus, we can conclude that there is a significant association between anxiety and hypertension. Here, the ‘Pearson Chi-Square’ statistic value is equal to 72.016.

Data: Chi_square_data.sav

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