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Introduction to Statistical Decision Theory Hardcover – March 27, 1995

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Product Details

  • Hardcover: 895 pages
  • Publisher: The MIT Press; First Edition edition (March 27, 1995)
  • Language: English
  • ISBN-10: 0262161443
  • ISBN-13: 978-0262161442
  • Product Dimensions: 7.3 x 2 x 10.2 inches
  • Shipping Weight: 3.8 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #2,339,827 in Books (See Top 100 in Books)

Editorial Reviews


"An excellent introduction to Bayesian statistical theory." Frank Windmeijer Times Higher Education Supplement

"This book is a classic.... The strengths of this text are twofold. First, it gives a general and well-motivated introduction to the principles of Bayesian decision theory that should be accessible to anyone with a good mathematical statistics background. Second, it provides a good introduction to Bayesian inference in general with particular emphasis on the use of subjective information to choose prior distributions." Mark J. Schervish Journal of the American Statistical Association

"This is the authoritative introductory treatise (almost 900 pages) on applied Bayesian statistical theory. It is self-contained and well-presented, developed with great care and obvious affection by the founders of the subject." James M. Dickey Mathematical Reviews

--This text refers to the Paperback edition.

About the Author

All of the authors are at Harvard University. John W. Pratt is William Ziegler Professor of Business Administration, Howard Raiffa is Frank P. Ramsey Professor of Managerial Economics, and Robert Schlaifer is William Ziegler Professor Emeritus.

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Most Helpful Customer Reviews

13 of 13 people found the following review helpful By Chad R. Bhatti on January 23, 2010
Format: Hardcover Verified Purchase
This is a very accessible introduction to Bayesian statistics and its applications in economics and management science. The book would make an interesting and useful two semester course at the sophomore or junior level. The mathematical prerequisites are small - some calculus, but the book manages to introduce basic probability, stochastic processes, statistical inference, large sample theory, the multivariate normal distribution, and topics related to economics such as utility functions, lotteries, decision trees and portfolio theory. These topics are useful to students in a wide variety of disciplines: economics, finance, computer science, electrical engineering, statistics, and students in the sciences which may end up in the bio/health sciences (medial decision making). In addition with the growing prevalence of Bayesian computation across disciplines, it seems like a lost opportunity not to offer such a course.
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0 of 12 people found the following review helpful By Teri Foster on March 25, 2013
Format: Paperback
Ordered the book for my boss. He likes the book. I am going to quit rating books because you have to many rules.
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