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The Beta-Binomial model is used to model binary data such as conversions or clicks (“did the user convert or not?”). I’ll also review the Normal-Normal model, which is used for continuous data (for example revenue per user). In the Beta-Binomial model we assume that the conversion rate Pᴀ has a Beta distribution with parameters α and β. A common choice for α and β is 1, which results with a uniform distribution (sometimes referred to as an “uninformative prior”). I discuss the choice of the prior in more detail in the appendix, but for now let’s continue as if they have already been chosen. (View Highlight)