Bayesian A/B Testing: not just “whether” B beats A, but “by how much”

In the article on classic A/B testing we saw how to compare two variants with the two-proportion test: we compute a statistic, get a p-value, and decide whether to reject the null hypothesis. It works, and it is the daily bread of anyone running online experiments. But there is a subtle gap between what the Continue reading "Bayesian A/B Testing: not just whether B beats A, but by how much "