Get startedGet started for free

Is a multiple comparisons correction needed?

Let's assume that you are an Analytics Engineer facing several experimental design scenarios where a multiple comparisons correction may be needed to avoid inflating the false positive error rate. Think about the conditions in each scenario and how the number of metrics, variants, or subcategories tested in each experiment might impact the need for a correction.

This exercise is part of the course

A/B Testing in Python

View Course

Hands-on interactive exercise

Turn theory into action with one of our interactive exercises

Start Exercise