AI engineering glossary · Statistics inference
What is effect size?
Effect size: A measure of how large a difference or relationship is, independent of sample size. Unlike a p-value, it tells you whether the change is big enough to matter. Reporting it alongside the p-value shows both whether an effect exists and how big it is.
Effect size: an example
A new onboarding flow raises seven-day retention from 40 to 43 percent, an effect of 3 percentage points.
Related terms
More Statistics inference terms
- Efficiency
- Estimator
- F-test
- False discovery rate
- Family-wise error rate
- Fisher information
- Fisher's exact test
- Frequentist inference
Where you learn it
Effect size is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.