October 2015
Beginner to intermediate
300 pages
7h 19m
English
Part of a statistician’s or data scientist’s goal is to be a champion of experiments, and one of the best tools for a data scientist is a well-designed split-test experiment. We’ve seen split-tests previously. In Chapter 2, we introduced Bayesian analysis of an A/B test on conversion rates for a Web site. This chapter will extend that analysis to new areas.
The fundamental idea in an A/B test is that we consider a perfect counterfactual universe, where the population under study is identical but subject to some treatment, then any differences between the populations after the study must be attributed to the treatment. In practice, we can’t spin up other universes, so we ...