Think Bayes: Bayesian Statistics in Python

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If you know how to program with Python andalso know a little about probability, you’re ready to tackle Bayesianstatistics. With this book, you'll learn how to solve statistical problems withPython code instead of mathematical notation, and use discrete probabilitydistributions instead of continuous mathematics. Once you get the math out ofthe way, the Bayesian fundamentals will become clearer, and you’ll begin toapply these techniques to real-world problems.

Bayesian statistical methods are becoming more common and more important, butnot many resources are available to help beginners. Based on undergraduateclasses taught by author Allen Downey, this book’s computational approach helpsyou get a solid start.

• Use your existing programming skills to learn and understand Bayesian statistics
• Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing
• Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey
• Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.