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Bayesian Decision Analysis: Principles and Practice Hardcover – November 15, 2010

ISBN-13: 978-0521764544 ISBN-10: 0521764548

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Bayesian Decision Analysis: Principles and Practice + Bayes' Rule: A Tutorial Introduction to Bayesian Analysis
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Product Details

  • Hardcover: 348 pages
  • Publisher: Cambridge University Press (November 15, 2010)
  • Language: English
  • ISBN-10: 0521764548
  • ISBN-13: 978-0521764544
  • Product Dimensions: 6.8 x 0.8 x 9.7 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 1.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #2,216,191 in Books (See Top 100 in Books)

Editorial Reviews

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 Magazine

Book Description

Real-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.

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Most Helpful Customer Reviews

3 of 4 people found the following review helpful By Alice on September 18, 2013
Format: Hardcover Verified Purchase
This may be a good book for academic purposes, but as a practitioner looking for an entry into the field, this book has been useless to me. I am a M.S. statistician with some very basic knowledge of Bayesian Analysis and the concepts of decision analysis, and I am needing to apply a Bayesian decision analysis. If you are in a similar situation - look elsewhere!
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