How do you use beta distribution to model user behavior in A/B testing?
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A/B testing is a common method to compare two versions of a product, feature, or design and measure their impact on user behavior. For example, you might want to test whether changing the color of a button increases the click-through rate. But how do you decide which version is better based on the data you collect? And how do you account for the uncertainty and variability in your sample? One way to answer these questions is to use beta distribution to model user behavior in A/B testing. In this article, you will learn what beta distribution is, why it is useful for A/B testing, and how to apply it in practice.
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