Use to test for independence or homogeneity of two categorical variables. If comparing only two groups with a binary outcome, refer to the Two Proportions Test and Confidence Interval guide.
The Contingency Table Analysis
- From an open JMP® data table, select Analyze > Fit Y by X.
- Click on a categorical variable from Select Columns, and click Y, Response (categorical variables have red or green bars).
- Click on another categorical variable and click X, Factor.
- Click OK. The Contingency Analysis output will display.
By defaut, a Mosaic Plot, Contingeny Table, and Chi-Square Tests are shown. See the Mosaic Plot and Contingency Table guide for more information.
Car Poll.jmp (Help > Sample Data Folder)


Chi-Square Tests
By default, JMP provides results for two chi-square tests under “Tests” – the Likelihood Ratio and Pearson.
- If both variables can be considered as response (Y) variables, these chi-square statistics test that the variables are independent.
- If one variable is considered a response (Y) and the other as a fixed factor (X), the tests are for homogeneity of Y across X.
Interpretation (using a significance level of 0.05):
• P-values for the two tests are given under Prob>ChiSq.
• Since the p-values are less than 0.05, we conclude that there is a significant difference in the probability of purchasing a particular
type of car for married and single adults (i.e., car choice is not homogenous across the two marital status groups).
The Expected Count and the contribution of each cell results to the Chi-Square Test Statistic was added to the Contingency Table by selecting that option under the Red Triangle.
Note: Additional analysis options are available under the Red Triangle including Analysis of Means for Proportions, Measures of Association, and Exact Tests.
Visit Basic Analysis > Contingency Analysis in JMP Help to learn more.