Performing a Kolmogorov-Smirnov test of a numeric column’s distribution across values of another column

A Kolmogorv-Smirnov test indicates whether the values of a numeric column tend to be distributed differently across two or more categories. Unlike an ANOVA test, it looks for differences in the entire distribution and not just the mean; however, the Kolmogorov-Smirnov test usually requires more observations than other tests in order to detect a difference.

To perform a Kolmogorov-Smirnov test:

1. In the Summary view, use the confidence slider to choose a desired confidence level
2. Choose the numeric column of interest on the left
3. Choose a category column that takes two or more values in the Covariate table
4. Click the button labeled Bars (or Dots) below the Covariate view
5. The result of the Kolmogorov-Smirnov test will appear in the Bottom Line

See also:

• Performing a Kolmogorov-Smirnov test of two or more numeric columns’ distributions
• Adjusting a p-value to account for multiple comparisons
• Performing a Mann-Whitney test of a numeric column’s median across two categories
• Performing a Kruskal-Wallis test of a numeric column’s median across values of another columns
• Performing a t-test of a numeric column’s mean across two categories
• Performing an ANOVA test of a numeric column’s mean across values of another column
• Viewing the correlation coefficient between two numeric columns
• Formatting descriptive and inferential statistics
• About the Summary view

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