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

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

Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in
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Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) Hardback - 2003 - 2nd Edition

by Andrew Gelman

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  • Title Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
  • Author Andrew Gelman
  • Binding Hardback
  • Edition number 2nd
  • Edition 2
  • Condition Used - Good
  • Pages 690
  • Volumes 1
  • Language ENG
  • Publisher Chapman and Hall/CRC, Boca Raton, FL, U.S.A.
  • Publication date July 29, 2003
  • Illustrated Yes
  • Bookseller's Inventory # ANAIS-158488388X
  • ISBN 9781584883883 / 158488388X
  • Weight 2.51 lbs (1.14 kg)
  • Dimensions 9.21 x 6.14 x 1.44 in (23.39 x 15.60 x 3.66 cm)
  • Size 9.5X6.5X1.5
  • Category Mathematics
  • Library of Congress subjects Bayesian statistical decision theory
  • Library of Congress Catalogue Number 2003051474
  • Dewey Decimal Code 519.542
  • Quantity available 1

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From the publisher

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:

  • Stronger focus on MCMC
  • Revision of the computational advice in Part III
  • New chapters on nonlinear models and decision analysis
  • Several additional applied examples from the authors' recent research
  • Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more
  • Reorganization of chapters 6 and 7 on model checking and data collection

Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

First line

By Bayesian data analysis, we mean practical methods for making inferences from data using probability models for quantities we observe and for quantities about which we wish to learn.

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