An intuitive and mathematical introduction to subjective probability andBayesian statistics. An accessible, comprehensive guide to the theoryof Bayesian statistics, Principles of Uncertainty presents thesubjective Bayesian approach, which has played a pivotal role in gametheory, economics, and the recent boom in Markov Chain Monte Carlomethods. Both rigorous and friendly, the book contains: Introductorychapters examining each new concept or assumption Just-in-timemathematics – the presentation of ideas just before they are appliedSummary and exercises at the end of each chapter Discussion ofmaximization of expected utility The basics of Markov Chain Monte Carlocomputing techniques Problems involving more than one decision-makerWritten in an appealing, inviting style, and packed with interestingexamples, Principles of Uncertainty introduces the most compellingparts of mathematics, computing, and philosophy as they bear onstatistics. Although many books present the computation of a variety ofstatistics and algorithms while barely skimming the philosophicalramifications of subjective probability, this book takes a differenttack. By addressing how to think about uncertainty, this book givesreaders the intuition and understanding required to choose a particularmethod for a particular purpose.