Introduction to Empirical Bayes: Examples from Baseball Statistics
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Introduction to Empirical Bayes: Examples from Baseball Statistics
Learn to use empirical Bayesian methods for estimating binomial proportions, through a series of intuitive examples drawn from baseball statistics. These methods are effective in estimating click-through rates on ads, success rates of experiments, and other situations common in modern data science.<br /><br />You'll learn both the theory and the practice behind empirical Bayes, including computing credible intervals, performing Bayesian A/B testing, and fitting mixture models. Each example is accompanied with visualizations to demonstrate the mathematical concepts, as well as R code that can be adapted to analyze your own data.
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