Chi-Square Calculator

Use this chi-square calculator to test relationships between categorical variables. It computes the Pearson’s chi-square statistic by comparing your observed counts to the values you would expect if there were no association between categories. The results include the overall χ² value, degrees of freedom, p-value, and an APA-style results format for publications.

In the chi-square calculator, start by entering the number of columns and rows, up to 5 X 5, and click Next. In the table that appears, enter your row and column labels, fill in your observed counts, and click Calculate. The calculator will display a table showing raw counts, expected counts (in parentheses), and each cell’s contribution. Below the calculator you’ll find additional resources about how this test works and interpretations. See all my Statistical Calculators!

Interpret the results from this chi-square calculator in relation to the null and alternative hypotheses for the test of independence:

• Null hypothesis: There are no relationships between the categorical variables. If you know the value of one variable, it does not help you predict the value of another variable.
• Alternative hypothesis: There are relationships between the categorical variables. Knowing the value of one variable does help you predict the value of another variable.

Therefore, if the calculator’s p-value is less than your significance level (e.g., 0.05), you can conclude that a relationship exists between the categorical variables.

Note: If you have less than 5 observations in any cell, you should use Fisher’s exact test instead because the chi-square results are unreliable.

For more information and examples about interpreting the chi-square calculators output, read my article, Chi-Square Test of Independence and an Example. To learn more about the calculation process, read How the Chi-Square Test of Independence Works.