Bayesian Analysis with Python - Third Edition

Table of Contents

Thinking Probabilistically  1.1 Statistics, models, and this book’s approach  1.2 Working with data  1.3 Bayesian modeling  1.4 A probability primer for Bayesian practitioners   1.4.1 Sample space and events   1.4.2 Random variables   1.4.3 Discrete random variables and their distributions   1.4.4 Continuous random variables and their distributions   1.4.5 Cumulative distribution function   1.4.6 Conditional probability   1.4.7 Expected values   1.4.8 Bayes’ theorem  1.5 Interpreting probabilities  1.6 Probabilities, uncertainty, and logic  1.7 Single-parameter inference   1.7.1 The coin-flipping problem   1.7.2 Choosing the likelihood   1.7.3 Choosing the prior   1.7.4 Getting the posterior   1.7.5 The influence of the prior ...