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Bayesian Statistics: An Introduction Paperback – September 4, 2012

ISBN-13: 978-1118332573 ISBN-10: 1118332571 Edition: 4th

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Bayesian Statistics: An Introduction + Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) + Doing Bayesian Data Analysis: A Tutorial with R and BUGS
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Product Details

  • Paperback: 486 pages
  • Publisher: Wiley; 4 edition (September 4, 2012)
  • Language: English
  • ISBN-10: 1118332571
  • ISBN-13: 978-1118332573
  • Product Dimensions: 6 x 0.9 x 9 inches
  • Shipping Weight: 1.3 pounds (View shipping rates and policies)
  • Average Customer Review: 2.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #1,175,390 in Books (See Top 100 in Books)

Editorial Reviews


“As a lifelong non-statistician and sporadic “user” of statistics, I have not come across another advanced statistics book (as I would characterize this one) that offers so much to the non-expert and, I’ll bet, to the expert as well. The book has my highest recommendation.”  (Computing Reviews, 7 January 2013)

From the Back Cover

Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.

This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples.

This edition:

  • Includes expanded coverage of Gibbs sampling, including more numerical examples and treatments of OpenBUGS, R2WinBUGS and R2OpenBUGS.
  • Presents significant new material on recent techniques such as Bayesian importance sampling, variational Bayes, Approximate Bayesian Computation (ABC) and Reversible Jump Markov Chain Monte Carlo (RJMCMC).
  • Provides extensive examples throughout the book to complement the theory presented.
  • Accompanied by a supporting website featuring new material and solutions.

More and more students are realizing that they need to learn Bayesian statistics to meet their academic and professional goals. This book is best suited for use as a main text in courses on Bayesian statistics for third and fourth year undergraduates and postgraduate students.

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Customer Reviews

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Most Helpful Customer Reviews

9 of 10 people found the following review helpful By tahabekir on September 17, 2013
Format: Kindle Edition Verified Purchase
It's incredibly difficult to learn anything from this book. Initially I thought I was having a difficult time because topics are complicated but when I read a few topics that I knew before hand I noticed the author has a terrible way of explaining (or lack of explaining) things. He just dumps a load of new notation and equations on you without properly explaining the logic behind.

I just read the EM (expectation maximization) chapter (close to the end) and I'm seriously angry. I read this topic from at least two different sources before and the way it's taught in this book is appalling. It's almost as if the author is trying to confuse you.

Whenever I look up the concepts allegedly taught in this book in wikipedia I have a much easier time understanding them. This should explain how terrible this book is.

To the author: sir you may or may not be a talented individual but please do not write anything, ever.
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4 of 4 people found the following review helpful By Hemant G. Muley on October 2, 2013
Format: Paperback Verified Purchase
I gave the highest rating to the Lee book because he develops the subject matter systematically, and there are no gaps in his reasoning. Moreover, the author's language is precise, and he supplies the motivation for each new concept. The companion website for this book will ensure your success, because solutions to various exercises are presented. All in all, the resources provided by Lee in this compact textbook are more than adequate to make a serious student do well in homework and exams. However, this is a textbook suitable only for those who have sufficient background in Probability and Calculus.
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0 of 1 people found the following review helpful By Xinchen C. on September 21, 2013
Format: Paperback Verified Purchase
I thought it is a good book, but I was wrong. There are lots of typo, and the statistical symbols in this book are rarely found in other books. It makes confusions when you try to connect between the knowledge you've learn and the material in this book.
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