---
product_id: 6543711
title: "Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science)"
price: "₹ 17398"
currency: INR
in_stock: true
reviews_count: 13
url: https://www.desertcart.in/products/6543711-bayesian-data-analysis-chapman-and-hall-crc-texts-in-statistical
store_origin: IN
region: India
---

# Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science)

**Price:** ₹ 17398
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- **What is this?** Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science)
- **How much does it cost?** ₹ 17398 with free shipping
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## Description

desertcart.com: Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science): 9781439840955: Gelman, Professor in the Department of Statistics Andrew, Carlin, John B, Stern, Hal S: Books

Review: Great Introduction to Bayesian Modelling - Excellent book. Right from the start it explains everything with good examples from authors' research in a very clear and understandable way. Good list of exercises at the end of each chapter (some are easy, some are hard) that really helps anyone using it for self study. Content has some minor overlap with another of Gelman's book, but that was fine with me. The book has a lot of good content and assumes previous knowledge on basic probability and statistics. Definitely recommended as a starter, refresher, self-study guide, textbook or even reference for anyone interested in bayesian modelling.
Review: Solid improvement and update to a Classic - 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.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #83,048 in Books ( See Top 100 in Books ) #5 in Statistics (Books) #55 in Probability & Statistics (Books) |
| Customer Reviews | 4.6 4.6 out of 5 stars (242) |
| Dimensions  | 7.3 x 1.4 x 10.1 inches |
| Edition  | 3rd |
| ISBN-10  | 1439840954 |
| ISBN-13  | 978-1439840955 |
| Item Weight  | 2.94 pounds |
| Language  | English |
| Part of series  | Chapman & Hall/CRC Texts in Statistical Science |
| Print length  | 675 pages |
| Publication date  | November 7, 2013 |
| Publisher  | Chapman & Hall |

## Images

![Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science) - Image 1](https://m.media-amazon.com/images/I/81YHoGwzyvL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great Introduction to Bayesian Modelling
*by D***M on February 6, 2015*

Excellent book. Right from the start it explains everything with good examples from authors' research in a very clear and understandable way. Good list of exercises at the end of each chapter (some are easy, some are hard) that really helps anyone using it for self study. Content has some minor overlap with another of Gelman's book, but that was fine with me. The book has a lot of good content and assumes previous knowledge on basic probability and statistics. Definitely recommended as a starter, refresher, self-study guide, textbook or even reference for anyone interested in bayesian modelling.

### ⭐⭐⭐⭐⭐ Solid improvement and update to a Classic
*by W***A on December 7, 2013*

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.

### ⭐⭐⭐⭐⭐ Excellent Book
*by C***G on March 25, 2014*

As a graduate student in econometrics, I found that this book provided a comprehensive introduction to the Bayesian analysis, from the very basic fundamentals to recent development in non-parametric analysis. It takes advantage in both scope and depth over many books about Bayesian analysis written to economists. As a result, I recommen this book to economists who need to do substantial Bayesian analysis in their research.

## Frequently Bought Together

- Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science)
- Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science)
- Data Analysis Using Regression and Multilevel/Hierarchical Models

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*Store origin: IN*
*Last updated: 2026-05-06*