Joseph B. Kadane

May 18, 2011
by Chapman and Hall/CRC

Textbook
- 504 Pages
- 28 B/W Illustrations

ISBN 9781439861615 - CAT# K12848

Series: Chapman & Hall/CRC Texts in Statistical Science

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*2011 Degroot Prize Winner!*

- Well-written and comprehensive introduction to theory of Bayesian statistics
- Each of the introductory chapters begins by introducing one new concept or assumption
- Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied
- Each chapter ends with a summary and exercises

**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. Both rigorous and friendly, the book contains:

- Introductory chapters examining each new concept or assumption
- Just-in-time mathematics – the presentation of ideas just before they are applied
- Summary and exercises at the end of each chapter
- Discussion of maximization of expected utility
- The basics of Markov Chain Monte Carlo computing techniques
- Problems involving more than one decision-maker

Written in an appealing, inviting style, and packed with interesting examples, **Principles of Uncertainty** introduces the most compelling parts of mathematics, computing, and philosophy as they bear on statistics. Although many books present the computation of a variety of statistics and algorithms while barely skimming the philosophical ramifications of subjective probability, this book takes a different tack. By addressing how to think about uncertainty, this book gives readers the intuition and understanding required to choose a particular method for a particular purpose.