This guide contains all of the ASC's statistics resources. If you do not see a topic, suggest it through the suggestion box on the Statistics home page.

- Home
- Excel - Tutorials
- ProbabilityToggle Dropdown
- VariablesToggle Dropdown
- Statistics BasicsToggle Dropdown
- Discussing Statistics In-text
- Z-Scores and the Standard Normal DistributionToggle Dropdown
- Accessing SPSS
- SPSS-TutorialsToggle Dropdown
- Effect SizeToggle Dropdown
- G*PowerToggle Dropdown
- ANOVAToggle Dropdown
- Chi-Square Tests
- CorrelationToggle Dropdown
- Mediation and Moderation
- Regression AnalysisToggle Dropdown
- T-TestToggle Dropdown
- Predictive Analytics This link opens in a new window
- Quantitative Research Questions
- Hypothesis TestingToggle Dropdown
- Statistics Group Sessions

This Chi-Square test is used to determine if there's a relationship between two categorical variables. Think of this as a non-parametric version of a correlation analysis. It can also be called the Test for Independence.

**Assumptions**

- Both variables must be nominal or ordinal.
- Each variable must have at least 2 independent groups.

**Running Chi-Square Test of Association in SPSS - Method 1**

NOTE: these steps are for raw data, ** not** summated frequencies (two-way table)

- Analyze > Descriptive Statistics > Crosstabs
- Move one variable into the "Row(s)" box and the other variable into the "Column(s)" box
- variable designation is up to the researcher

- Click on the "Statistics" button to select additional statistics to include with the output
- ensure "Chi-square" is checked
- click the "Continue" to return to the main dialog box

- Click on the "Cells" button
- ensured Observed, Row, Column, and Total boxes are all checked
- click the "Continue" button to return to the main dialog box

- Click OK to run the test

**Running Chi-Square Test of Association in SPSS - Method 2**

NOTE: these steps are for summated frequencies (two-way table), ** not** raw data

- Ensure you have 3 "variables" created so that all cells from the table are represented
- Categorical variable 1 - enter this data so that each entry appears once per number of categories in variable 2
- ie - A, A, A, B, B, B, C, C, C - if there are 3 levels to the other variable

- Categorical variable 2 - enter this data so that each level is paired with each level of variable 1
- ie - 1, 2, 3, 1, 2, 3, 1, 2, 3 - so reading across the rows shows A1, A2, A3, etc.

- Frequency - enter the number of people in each cell
- ie. How many people were in group A and group 1?

- Categorical variable 1 - enter this data so that each entry appears once per number of categories in variable 2
- Data > Weight Cases
- Select "Weight cases by" radio button
- move the Frequency variable into the box
- click OK to return to the data sheet

- Analyze > Descriptive Statistics > Crosstabs
- Move one variable into the "Row(s)" box and the other variable into the "Column(s)" box
- variable designation is up to the researcher

- Click on the "Statistics" button to select additional statistics to include with the output
- ensure "Chi-square" is checked
- click the "Continue" to return to the main dialog box

- Click OK to run the test

**Interpreting the Output**

- [variable]*[variable] Crosstabulation (the variable names will reflect the variables you entered for analysis)
- This table presents the counts (and percentages if selected) for each cell

- Chi-Square Tests
- provides the results of the chi-square test
- used to make a decision about the null hypothesis

- Symmetric Measures (if selected)
- this table provides measures of association and their significance

**Reporting Results in APA Style**

A chi-square test of association was conducted to determine if there is a relationship between gender and swimming abilities. There was sufficient evidence to suggest that women are more likely to swim than men, *X*^2(1, *N *= 101) = 8.8, *p* < .05.

- Last Updated: Nov 18, 2023 1:41 PM
- URL: https://resources.nu.edu/statsresources
- Print Page