Customer Reviews


20 Reviews
5 star:
 (7)
4 star:
 (3)
3 star:
 (4)
2 star:
 (4)
1 star:
 (2)
 
 
 
 
 
Average Customer Review
Share your thoughts with other customers
Create your own review
 
 

The most helpful favorable review
The most helpful critical review


26 of 28 people found the following review helpful
5.0 out of 5 stars Very Excellent, but non-statisticians should start elsewhere
Gelman's book is an excellent and complete introduction to Bayesian methods. It covers a number of topics not touched by other intros I've read, and focuses much more on regression and ANOVA than other texts.

There are two downsides, coming from someone in psychology. First, the book seems to hover between an introductory text and a more advanced one. The...
Published on June 5, 2006 by MrDNA

versus
112 of 130 people found the following review helpful
3.0 out of 5 stars A good introductory book, but...
I read the other reviews and agree with them to some extent. This is

a good introduction to applied Bayesian analysis. Lots of

good examples, illustrations and exercises.

If you are the kind of person who learns by way of examples, then

this might be the text book for you. If you are looking for the

bigger picture,...
Published on January 25, 2005 by Zoro


‹ Previous | 1 2 | Next ›
Most Helpful First | Newest First

112 of 130 people found the following review helpful
3.0 out of 5 stars A good introductory book, but..., January 25, 2005
By 
Zoro (Somewhere) - See all my reviews
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
I read the other reviews and agree with them to some extent. This is

a good introduction to applied Bayesian analysis. Lots of

good examples, illustrations and exercises.

If you are the kind of person who learns by way of examples, then

this might be the text book for you. If you are looking for the

bigger picture, then you will be lost here. There is very little in the way

of theory. Why is this the right method? What is gained theoretically

over a frequentist method? What are the theoretical properties of the

proposed approach? To a large extent these kinds of questions remain a mystery.

In terms of flexibility an applied Bayesian approach has some decided

advantages. However, in terms of theory

it's almost as if the authors want you to believe that once

you adopt the Bayesian approach then the benefits of averaging

by way of using a prior will always be the right thing to do.

You could argue that advanced questions like this are better suited for

a more advanced text book. I tend to ask more out of a book.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


26 of 28 people found the following review helpful
5.0 out of 5 stars Very Excellent, but non-statisticians should start elsewhere, June 5, 2006
By 
MrDNA (Spokane, WA) - See all my reviews
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
Gelman's book is an excellent and complete introduction to Bayesian methods. It covers a number of topics not touched by other intros I've read, and focuses much more on regression and ANOVA than other texts.

There are two downsides, coming from someone in psychology. First, the book seems to hover between an introductory text and a more advanced one. The topics covered are mostly introductory, but the examples aren't always entirely easy to follow. A tighter integration with the R and Bugs code would help. Perhaps a section at the end of the chapters containing a code example for each topic would be ideal. It's not that the topics themselves are necessarily opaque, but Gelman moves too fast at times, making it hard to think in terms of notation, theory, experimental design AND code at the same time (for those of us constantly thinking about how this affects our own research).

Second, as a general rule, this book is outside the ken of most psychologists. This is unfortunate since the methods are ideal for our discipline, and since many psychologists already perceive a large barrier of entry to statistics. As a psychologist with minimal undergraduate training in stats, I would (and did) start with a standard statistics book like Casella and Berger, and then move on to a gentler introduction to Bayesian methodology, like _Bayesian Methods: A Social and Behavioral Sciences Approach_ by Jeff Gill. Also, you can barely do anything in this book with SPSS so you'll have to learn R and Bugs.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


27 of 31 people found the following review helpful
2.0 out of 5 stars I did not care for this book., July 19, 2009
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
I used this book for an introductory graduate course in Bayesian Data Analysis. I found aspects of the book to be needlessly confusing due to a lack of mathematical clarity in the text. The mathematical level of this book is very low. However, the book proceeds to perform Bayesian data analysis using multivariate normal theory and generalized linear models, without developing any background. It seems contradictory to assume such a low mathematical level, but also assume that the reader knows particular results from multivariate normal theory and glm. The verbal orientation of the book can be frustrating, especially since a verbal description could adequately suggest more than one model formulation. I would not recommend this book as a text book. This book seems best served as an auxiliary book for examples. If you want to learn Bayesian statistics, you need to buy "The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation" by Christian P. Robert. Robert's book is the correct place to start.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


7 of 7 people found the following review helpful
5.0 out of 5 stars Best Introduction to Applied Bayesian Analysis Out There, May 4, 2010
Verified Purchase(What's this?)
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
I've read many, many books on Bayesian analysis at this point. Gelman's book is head-and-shoulders above the rest as an introduction to Bayesian analysis. His book does an outstanding job of introducing the model and the motivation behind the parameters from a very intuitive perspective. Many other Bayesian statisticians seem to enjoy the formulation of the problem so much (count myself as one of them) that they get lost in the beauty of the math and it becomes difficult to effectively convey why the model was selected and how to infer the parameters.

Gelman's book is the first book I've read that strikes a balance between the formulation and the explanation.

This book is not for those looking for the theoretical motivation behind Bayesian analysis, or those interested in absorbing the bounds of asymptotic performance, etc. Christian Robert's "The Bayesian Choice", or his other co-authored books, is a much better place for those who have already gotten their minds around Bayesian statistics and want to explore the gory details.

I don't dock Gelman's book for the limited amount of formal propositions/theorems/proofs because I feel that there are plenty of other decent books that do that well. But Gelman's book fills a much-needed gap for those interesting in starting out in Bayesian statistics.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


7 of 7 people found the following review helpful
5.0 out of 5 stars Turns potentially dry material in something interesting, April 5, 2010
By 
Verified Purchase(What's this?)
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
This book, more than any statistics book that i've read, is full of beautiful heuristic commentary which is also useful to a practitioner.
I've found that an excellent supplement is "Bayesian Modeling Using WinBugs" by Ntzoufras. Gelman et al. provide wordy but enlightening explanations of Bayesian concepts with just the right amount of Math for someone that wants get their hands dirty and analyze some data with competance. The book is full examples with nice discussions from someone with a deep understanding of statistical inference. What these examples sometime lack is details of how the results were got.

This is where Ntzoufras comes in.

Ntzoufras complements Gelman perfectly by offering a book full of detailed examples with a lot of R and WinBugs code.
Jim Albert's book, "Bayesian Computation with R" is also a very good supplement to Part III of Gelman et al. as is Albert's LearnBayes R package.

Gelman has also co-written an R package called "arms" which can also supplement some of this book.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


4 of 4 people found the following review helpful
4.0 out of 5 stars Decent for engineers, August 29, 2008
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
This seems to be the best book out there for learning Bayesian statistics. The book is well written and usually quite clear. I think it be better organized, and pointers to programming examples would be welcomed, especially in the introductory computation section.

I am an engineer, and unfortunately for me, this book is geared towards social scientists. However, no other bayesian statistics books currently teach from an engineering perspective, so this is your best be if you are an engineer.

This book does assume a good deal of familarity with mathematical statistics, which many engineers do not have. However, it is possible to get though it by looking this up on wikipedia.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


3 of 3 people found the following review helpful
4.0 out of 5 stars An introduction to bayesian statstics, November 8, 2009
Verified Purchase(What's this?)
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
The book introduces the basis of bayesian statistics. There are lots of examples and many applications realized by R software or WinBugs.
Topcis about hierarcical models and MonteCarlo markov Chain method are explained clearly.
I think that a minus prerequisite is a good knowledge of classical stastical inference, stastical models and software packaging as R, stata or Win Bugs.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


2 of 2 people found the following review helpful
1.0 out of 5 stars Don't purchase the Kindle edition, November 10, 2013
Verified Purchase(What's this?)
The transcription of formulae in the Kindle edition is unusably bad, especially when in-line. Problems include missing accents over variables, missing or mis-transcribed operators, and Latin letters inconsistently substituted for Greek letters. Save yourself the trouble and stick with the hardback edition.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


4 of 5 people found the following review helpful
4.0 out of 5 stars Very informative, could use more explicit calculations, July 8, 2011
Verified Purchase(What's this?)
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
This is a book on Bayesian data analysis, but should not be someone's first book on Bayesian methods. It should also not be someones first book on statistical modeling.

The authors do a good job of building up from simple models to ones with more and more generalization. They also do a good job of adding in real life data sets, and walking you through how they modeled the data sets, verified the results, sampled various posterior distributions, etc.

The one aspect of the book that I found a little unbalanced was that it was wordier than mathematical/coded. In one sense that's a virtue of the authors, many mathematics books drill you with hundreds of pages of dense math, and I'm sure by avoiding that path, the book's audience is larger. But I still found myself, particularly when first being introduced to a concept, wanting to see an explicit simple calculation, just to make sure that I fully understood the basic concept.

Along the same lines of the past paragraph, I found Albert's 'Bayesian Computation with R' to be a good supplement. It is rich in code, and thin in text, so the two books balance each other well. I typically found myself reading a chapter in this text, then finding the associated chapter in Albert's book, then coding up some additional examples on my own.

All and all good stuff. I'd give it 4.5 stars, and will flip a coin to see if that ends up being recorded as a 4 or 5! tails it was...
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


1 of 1 people found the following review helpful
2.0 out of 5 stars Poor Motivation, February 16, 2013
This review is from: Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover)
This book is completely inadequate in my view. I'm using this text for a graduate course in Bayesian Stat. and it is extremely frustrating. The author gives almost no theoretical motivation for why one should use the methods described in the text. For example, what makes Gibbs sampling better or worse than Metropolis-Hastings. I read the chapter on this and still had to look at a Wikipedia article to gain this basic insight. The wiki also did a better job of theoretically justifying the algorithm. I'm sorry but that is just pitiful. Try something else, even if you're a beginner.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


‹ Previous | 1 2 | Next ›
Most Helpful First | Newest First

Details

Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Used & New from: $45.99
Add to wishlist See buying options
Search these reviews only
Rate and Discover Movies
Send us feedback How can we make Amazon Customer Reviews better for you? Let us know here.