An intuitive and mathematical introduction to subjective probability and Bayesian statistics.An accessible, comprehensive guide to the theory of Bayesian statistics, Principles of Uncertainty presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.

chapter 1|28 pages


chapter 2|50 pages

Conditional Probability and Bayes Theorem

chapter |38 pages

Discrete Random Variables

chapter 4|68 pages

Continuous Random Variables

chapter |48 pages


chapter 6|34 pages

Normal Distribution

chapter 7|32 pages

Making Decisions

chapter 8|36 pages

Conjugate Analysis

chapter 9|16 pages

Hierarchical Structuring of a Model

chapter 10|28 pages

Markov Chain Monte Carlo

chapter 11|56 pages

Multiparty Problems

chapter |12 pages

Exploration of Old Ideas

chapter 13|2 pages

Epilogue: Applications