Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science), 3rd Edition by Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin – Hardcover (ISBN: 9781439840955)

By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin

Bayesian Data Analysis, 3rd Edition is one of the most influential and widely respected textbooks in modern Bayesian statistics and statistical modeling. Published as part of the Chapman & Hall/CRC Texts in Statistical Science series, this landmark reference combines rigorous theoretical foundations with practical applications used across statistics, machine learning, economics, social sciences, medicine, and data science research.

Widely adopted in graduate programs and advanced quantitative research environments, the book presents Bayesian inference through real-world modeling examples, computational methods, hierarchical models, regression techniques, and predictive analysis. It is considered an essential resource for advanced statistical education and professional data analysis.

What This Book Does

This book teaches Bayesian statistical reasoning and modern data analysis methods while helping readers develop practical skills in probabilistic modeling, inference, prediction, hierarchical modeling, and computational Bayesian techniques.

Key Features

• Comprehensive treatment of Bayesian statistics and inference
• Strong integration of theory, computation, and applied modeling
• Coverage of hierarchical models, regression, and predictive analysis
• Widely adopted in graduate statistics and data science programs
• Real-world examples across multiple research disciplines

Who Should Use This Book?

• Graduate students in statistics, data science, and machine learning
• Researchers performing advanced quantitative analysis
• Data scientists and applied statisticians
• Universities and quantitative research departments
• Institutions purchasing advanced statistical textbooks in bulk

Why It’s Essential

• Considered one of the foundational texts in Bayesian statistics
• Combines theoretical rigor with practical data-analysis applications
• Highly influential in modern statistical and machine learning education
• Essential resource for advanced quantitative modeling and research

A landmark reference for Bayesian statistics, probabilistic modeling, and modern data analysis.
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Product Details

• ISBN-13: 9781439840955
• Edition: 3rd
• Authors: Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin
• Publisher: Chapman & Hall/CRC
• Format: Hardcover
• Pages: 675
• Condition: New
• Price: $56.99
• Minimum Order: 5 Copies
• Availability: In Stock

TOC Highlights

• Bayesian Inference and Probability Foundations
• Regression and Hierarchical Modeling
• Markov Chain Monte Carlo (MCMC) Methods
• Model Checking and Predictive Analysis
• Advanced Bayesian Data Analysis Applications

FAQs

• Is this considered a standard Bayesian statistics textbook?
  Yes. It is one of the most widely respected and influential books in Bayesian data analysis.
• Does the book include computational Bayesian methods?
  Yes. It covers MCMC methods, hierarchical modeling, and practical computational approaches.
• Is this suitable for machine learning and data science students?
  Yes. The book is highly relevant for statistics, machine learning, AI, and advanced data science study.
• Do you support institutional and bulk orders?
  Yes. Bulk orders are supported for universities, research programs, and academic departments.