A/B testing, also known as split testing, helps businesses optimize conversion rates by experimenting with different webpage versions. The post compares frequentist and Bayesian methods for analyzing A/B test results. It highlights the limitations of the Chi2 test in frequentist settings and demonstrates Bayesian modeling using
Table of contents
An Introduction to Bayesian A/B TestingComparing Conversion RatesModel Arbitrary Data-generating ProcessesConclusionSort: