Know whether your A/B test is worth acting on.
Evaluates experiment results and plans sample sizes so users can make decisions using statistical significance, effect sizes, and practical impact.
When to use it
Use to check observed differences, size an experiment before launch, or interpret statistical test results.
Give it experiment numbers or an experiment-sizing question; it returns a statistical report with interpretation and decision guidance.
Requires Python 3 to run the bundled statistical scripts; the hypothesis tester uses only the standard library.
No additional actions listed.