Bayesian Decision Analysis (Principles And Practice)

Bayesian Decision Analysis (Principles And Practice)

Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics.Review"[L]et me stress that the design and the printing of the book are both of the highest quality, numerous tree graphs appearing seamlessly at the right place [making captions superfluous], different fonts making parts more coherent and so on. I thus hope it is obvious I strongly recommend reading the book to all involved in any level of decision management! Or teaching it."Xi'an's Og Blog"The preface explains that the book is intended as a course resource for mathematically sophisticated undergraduates and students in a statistics master's program. It would serve this purpose admirably and would be a very good reference book for all researchers in this field."R. Bharath, emeritus, Northern Michigan University for Choice MagazineBook DescriptionA textbook and guide to conducting Bayesian decision analysis of sometimes very complex policies and collaborative decisions.Book DescriptionReal-world decisions involve numbers, but they also involve people. Bayesian decision analysis gives a principled framework for reconciling the two. This textbook explains how to use statistical theory, psychology and algorithms to guide decision makers so that they can marshal available evidence and defend their actions.About the AuthorJim Q. Smith is a Professor of Statistics at the University of Warwick.