Using data science with A/B tests: chi-squared testing

by Jeff Rajeck
In my previous posts about A/B testing, I made the case that you need to consider the math behind A/B testing, or risk having invalid, or even wrong, results. My first suggestion is to use sample sizing, but that requires a lot of tests. Here's how to do something similar without nearly as many. With just a little bit of analysis you can check the validity of your A/B test b ...Read the full article