A Kolmogorv-Smirnov test indicates whether the values of two or more numeric columns tend to be distributed differently. 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:

- In the Summary view, use the confidence slider to choose a desired confidence level
- Command-click two or more numeric columns of interest on the left
- Click the button labeled
*Bars*(or*Dots*) below the Covariate view - The result of the Kolmogorov-Smirnov test will appear in the Bottom Line

See also:

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