A/B Testing Conversion Rates

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Using the Beta-Binomial model, we introduce a common pattern to perform Bayesian A/B testing. There are three strong reasons to prefer Bayesian A/B testing over traditional hypothesis testing: uncertainty visualisation, interpretable statistics and more flexibility of computing additional statistics.


  • What is A/B testing?
  • How do we use Bayesian statistics in A/B testing?
  • How do we determine if group A is better than group B?
  • And by how much is group A better than B?


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