Such a great article with excellent visualizations and animations. Thanks for sharing. I had built a simple python machine learning estimator using gradient descent, its amazing how it ties in nicely with your article. Here is a link to it:
Anyone who’s run an A/B test knows statistics has something to say about whether it’s A or B that wins. The nice thing about Bayesian A/B testing is that it’s (relatively) clear how we make that decision.
Confidence intervals (CIs)provide a means to judge point estimates based on a sample from the population.