This article provides a comprehensive discussion of the chi-square test of independence, the assumptions, and a step-by-step procedure on how to run the **chi-square test in **SPSS.

## Definition: What is a Chi-Square Test of Independence?

A chi-square test of independence is a *non-parametric statistical test* that is widely used in research to determine whether there is an association between categorical variables. The chi-square test of independence is also called a chi-square test of Association. Thus, by performing a chi-square test of independence in SPSS, you can be able to determine whether there is an association between any two categorical variables.

You can learn more about non-parametric tests in our article: Difference between parametric and non-parametric tests

## Chi-Square Test of Independence Example

Consider a scenario where you wish to determine whether there is an association between education level (primary, secondary, and tertiary) and Employment status (Unemployed, Employed). In this case, performing a chi-square test of independence can allow you to determine whether there is a relationship between education level and employment status.

## Chi-Square Test of Independence Assumptions

Before deciding to use a chi-square test of independence in your research, you need to make sure that your data meets the two main assumptions of a chi-square test of independence. Testing these assumptions is mainly important because it allows you to validate why you performed a chi-square test of independence and not the chi-square goodness of fit. If these assumptions are not met, then conducting a chi-square test of independence will yield inaccurate and unreliable results.

The two main assumptions are:

**Categorical Variables**– The two variables should be categorical. This means they should be measured using either a nominal or ordinal level of measurement.**Each Categorical Variable should have two or more independent categories**– For instance, if you want to test where there is an association between gender and employment status, then these variables meet this assumption because: Gender has two categories (Male/Female), and Employment status (Not-employed/Employed).

## Test Procedure for Performing a Chi-Square Test in SPSS [Chi-square test of independence]

Follow these 6 simple steps to run a chi-square test of independence (Association) in SPSS

**Step 1**: Click**Analyze > Descriptives Statistics > Crosstabs**as shown below

**Step 2**: Move one of the categorical variables into the Row(s): box and the other categorical variable into the Column(s): box. as shown below.

**Step 3**: Click on the**Statistics Button**and Select the*Chi-square*and*Phi and Cramer’s V*options, as shown below: The Chi-square will output the chi-square test of independence value, while the Phi and Cramer’s V will output the Effect Size of the chi-square test of independence.

**Step 4**: Click**Continue****Step 5**: Click the**Cells Button**and Select Observed from the –**Counts Section**. Also, from the**Percentages Section**, Select Row, Column, and Total, as shown below:

**Step 6**: Click theButton and Then, the**Continue**button to generate the chi-square test of independence Results.*OK*

Struggling with calculating a chi-square test of independence by hand? Learn more about the chi-square test of independence from our article on: mastering the chi-square test of independence.