Introduction to Empirical Bayes: Examples from Baseball Statistics

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David Robinson
62 ratings

Learn to use empirical Bayesian methods for estimating binomial proportions, through a series of examples drawn from baseball statistics. These methods are effective in estimating click-through rates on ads, success rates of experiments, and other examples common in modern data science. You'll learn both the theory and the practice behind empirical Bayesian methods, including computing credible intervals, performing Bayesian A/B testing, and fitting mixture models. Each example comes with R code that can be used to analyze your own data.

To learn more about the book and its content, see the announcement here:

http://varianceexplained.org/r/empirical-bayes-book

  • Size
    13.6 MB
  • Length
    142 pages
  • Size13.6 MB
  • Length142 pages

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Introduction to Empirical Bayes: Examples from Baseball Statistics

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