Think Bayes: Bayesian Statistics Made Simple is an introduction to Bayesian statistics using computational methods. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops.
Topics included: Bayes’s Theorem • Computational Statistics • Estimation • More Estimation • Odds and Addends • Decision Analysis • Prediction • Observer Bias • Two Dimensions • Approximate Bayesian Computation • Hypothesis Testing • Evidence • Simulation • A Hierarchical Model • Dealing with Dimensions.
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Publisher: Green Tea Press
Published: August 2016
Format(s): PDF, HTML(Online)
File size: 2.28 MB
Number of pages: 213
Download / View Link(s): PDF, Online