What ANOVA is not: A t-test. While similar, a t-test allows for the comparison of the mean across only two groups. Multiple two-sample t-tests result in an increase in the likelihood of a type I error.
Why ANOVA matters: Comparing the results of multiple experiments—multiple A/B tests or even test variations—is very useful for optimization. The ANOVA method provides a durable approach to making such comparisons in situations where only the difference in experiment outcome is of interest.
Enjoy this post? Download all 200+ terms!