An analysis of variance (ANOVA) test indicates whether the mean of a numeric column appears to vary across category values or groupings.

To perform an ANOVA test:

- In the Summary view, use the confidence slider to choose a desired confidence level
- Choose the numeric column of interest on the left
- Choose the category column of interest in the Covariate table
- Click the button labeled
*t-test*below the Covariate view - The result of the ANOVA test will appear in the Bottom Line

If only two category values are present, a two-sample t-test will be performed instead. (With two categories, two-sample t-tests are equivalent to ANOVA tests.)

See also:

- Performing an ANOVA test of three or more numeric columns’ means
- Performing a two-way ANOVA test of a numeric column’s mean across values of two other columns
- Performing a repeated measures ANOVA test of three or more numeric columns’ means
- Performing a t-test of a numeric column’s mean across two categories
- Adjusting a p-value to account for multiple comparisons
- Performing a Kruskal-Wallis test of a numeric column’s median across values of another columns
- Performing a Kolmogorov-Smirnov test of a numeric column’s distribution across values of another column
- Viewing the correlation coefficient between two numeric columns
- Partitioning a non-category covariate into discrete groups in the Summary view
- Formatting descriptive and inferential statistics
- About the Summary view