Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) 3rd Edition

by Andrew Gelman (Author), John B. Carlin (Author), Hal S. Stern (Author),

34 customer reviews

ISBN-13: 978-1439840955

ISBN-10: 1439840954

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Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors―all leaders in the statistics community―introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.

New to the Third Edition

Four new chapters on nonparametric modeling
Coverage of weakly informative priors and boundary-avoiding priors
Updated discussion of cross-validation and predictive information criteria
Improved convergence monitoring and effective sample size calculations for iterative simulation
Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation
New and revised software code

The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)

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Product Details

Series: Chapman & Hall/CRC Texts in Statistical Science (Book 106)
Hardcover: 675 pages
Publisher: Chapman and Hall/CRC; 3 edition (November 1, 2013)
Language: English
ISBN-10: 1439840954
ISBN-13: 978-1439840955
Product Dimensions: 1.2 x 7.5 x 10.2 inches
Shipping Weight: 2.9 pounds (View shipping rates and policies)
Average Customer Review: 4.6 out of 5 stars See all reviews (34 customer reviews)
Amazon Best Sellers Rank: #31,859 in Books (See Top 100 in Books)
- #48 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics
- #89 in Books > Science & Math > Mathematics > Applied > Probability & Statistics

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Customer Reviews

4.6 out of 5 stars

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Top Customer Reviews

Solid improvement and update to a Classic

ByWayne Foltaon December 7, 2013

Format: HardcoverVerified Purchase

What can you say when a classic like this is updated? The original was THE reference on the topic and this one expands on it and adds all kinds of little things they've thought about over the last 15+ years.

They've added chapters on Basis Function models, Gaussian Process models, Finite Mixture models, and Dirichlet Process models, and also lots of important but small concepts that we've previosly seen only in places like Andrew's blog, including things like boundary-avoiding priors. The coding example Appendix C has also been reworked to use Stan rather than BUGS.

The physical layout of the book has been improved as well. It's the same thickness, but slightly larger in the other two dimensions and with a smaller bottom margin, which I think gives a much better amount of information per page. The only thing I could ask for layout-wise is to have chapter/section numbers at the top of each page to make it quicker to find something.

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Don't buy the Kindle version!

Bylson June 23, 2014

Format: Kindle EditionVerified Purchase

It's not possible to read pages side-by-side on Kindle for PC. "Appendix A, Table A.1" is laid out across left and right pages in the 2nd edition. The 3rd (Kindle) edition can be viewed only page by page (affects new Table A.1 entries for Lognormal, LKJ correlation, Logistic, Log-logistic distributions). BTW, old people like me need to read digital text on large screens -- or wear reading glasses. I'm probably going to return my Kindle version of the 3rd edition for the hardcover (it's that good!). I didn't download the Kindle sample, but I doubt that the sample would have revealed the side-by-side page reading problem unless "Appendix A, Table A.1" was part of the sample.

0Comment 34 people found this helpful. Was this review helpful to you?YesNo

More accessible than I imagined.

ByNathan A. EdwardsVINE VOICEon October 14, 2014

Format: HardcoverVine Customer Review of Free Product( What's this? )

It seems that I am in the minority among reviewers in that this is my first experience with any iteration of this text. I will also admit that I am in the unusual demographic of applied statistics hobbyists. After reading the reviews of others, I realized that if an understanding of the Bayesian approach is to be pursued, this is the text to have.

I don't mind saying that I was intimidated by how quickly the text ramps up from introduction to application. I suffered no shortage of having to reference outside material to catch my bearings, but this is due to my own unorthodox path to this text. It is probably only due to the repeated use of real-world examples and a down-to-earth writing style that I am able to keep up at all.

Realizing how little I know, and how much I am able to glean from this text - which should be way beyond my comprehension - I can confidently say that this text is about as accessible as it gets without watering down the subject. I can't even imagine what a boon this text must be to those who have a broader educational foundation to build upon!

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The definitive book on the topic

ByJason StokesVINE VOICEon October 9, 2014

Format: HardcoverVine Customer Review of Free Product( What's this? )

I grew up in the frequentist world, learning frequentist ways, using my p-values like a diligent little statistician. A few years ago, I was introduced to...the other. Mostly through more basic books, talking broadly about Bayesian theory and its place in the world. Picked up an older version of this book and sat down with some far more educated people to really get it. I get it.

This is THE definitive book on Bayesian analysis. It is not for the faint of heart, or the light of math. If you're looking for an introductory topic and you don't have deep mathematical skills and knowledge, this isn't for you. If you want to dive in deeply to this at a graduate level, then this is what you should buy.

Many examples worked through, multiple models, and plenty of symbols to confuse the uninitiated.

11 comment 20 people found this helpful. Was this review helpful to you?YesNo

Great reference, but not for introduction

ByHyokun Yunon June 18, 2015

Format: HardcoverVerified Purchase

My impression from people around me was that this book is the canonical textbook for those who want to get into Bayesian statistics. After having read this book from cover to cover, however, I do not think it is a good idea to start learning Bayesian statistics with this book, as it covers very wide range of topics and therefore does not get into much technical depth for most of them. I think this book is ideal for someone like me who has very basic understanding of Bayesian statistics but would like to get some exposure to variety of existing tools in the literature so that when some of them become needed at certain point of my career, I can reopen this book and follow its references to learn enough to actually use them.

The stance of this book is very practical, and it is great to get a glimpse of how these grand-master Statisticians approach data analysis. First few chapters regarding the underlying philosophy of Bayesian statistics is also brilliantly written, a must-read for any Statistician.

I was somewhat disappointed with changes in the third edition though. The addition of Gaussian Processes and other advanced topics is greatly advertised, but I found these new chapters to be relatively poorly written compared to those in the previous edition; notations are not consistent with previous chapters, and clarity of writing is disappeared. It was a stupid idea to buy the new edition while having the second edition.

0Comment 12 people found this helpful. Was this review helpful to you?YesNo

Introduction and Thorough Discussion of Bayesian Statistics. My Print Had Some Legibility Problems

ByIra LaefskyVINE VOICEon September 22, 2014

Format: HardcoverVine Customer Review of Free Product( What's this? )

This book provides a short one chapter introduction to the use of Bayesian Analysis suitable for someone who has completed elementary statistics in an undergraduate program. The body of the book which is well illustrated by examples requires a significant background in statistics, calculus and linear algebra. Graphics and application examples are provided for these topics.

One physical criticism of the book (which may be limited to my copy and a given batch), is the light grey type making up much of the book. One would expect a high level of legibility in an expensive reference work.

11 comment 12 people found this helpful. Was this review helpful to you?YesNo

Most Recent Customer Reviews

Too Many Words

The text in this book seems overtly redundant/irrelevant; many details (words, sentences, even paragraphs) can be dropped without affecting the content.

Published 1 month ago by Ying-Ting Lin

The reference source for Bayesian Data Analysis

This is my go to book for looking up information I need on Bayesian data analysis. Everything is covered, and is quite easy to follow for the most part.Read more

Published 1 month ago by Ronald J. Legere

Don't be afraid!

While ordering this book for school, my first qualm was that it comes from an international seller. I was concerned that this edition wouldn't be up to proper standards or that...Read more

Published 3 months ago by Amazon Customer

Five Stars

The bible.

Published 3 months ago by Tony Fagan

Not the Best for Beginners but an Excellent Resource

Although Gelman's book on Bayesian data analysis may be a bit overwhelming for someone new to statistics, it is well written and approachable if you are already mathematically...Read more

Published 3 months ago by Mary Frame

Two Stars

Nothing special

Published 4 months ago by Amazon Customer

Nonetheless it does cover a lot of material and can still provide good guidance even if one doesn't fully grasp the underlying .

I have a decent econometrics background but I still found much of the book very difficult to understand. People smarter than I might get more out of it.Read more

Published 11 months ago by thinkingotherthings

Five Stars

All very well, I received the books without problems and very son too

Published 1 year ago by Hugo Bisceglia

Great experience.

A+. Great experience.

Published 1 year ago by John Dalby

Very useful to

We used it as textbook.
Very well written, combines theory and model setup.
Worth the price. Very useful to me

Published 1 year ago by Xin

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