Bayesian Inference in Statistical Analysis

Name: Bayesian Inference in Statistical Analysis
SKU: 2082675
Price: 496.00 NZD
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Paperback / softback

Series:

Wiley Classics Library

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Description

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Author Biography:

GEORGE E. P. BOX, PhD, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin, Madison. His lifelong work has defined statistical analysis, while his name and research is a part of some of the most influential statistical constructs, including Box & Jenkins models, Box & Cox transformations, and Box & Behnken designs. Dr. Box is the coauthor of a number of Wiley books, including most recently, Statistical Control by Monitoring and Adjustment, Second Edition; Response Surfaces, Mixtures, and Ridge Analyses, Second Edition; and Improving Almost Anything: Ideas and Essays, Revised Edition. NORMAN R. DRAPER is professor emeritus at the University of Wisconsin, Madison, in the Department of Statistics. His research interests include Experimental Design, Linear Models, and Nonlinear Estimation.

Release date NZ

April 21st, 1992

Author

Audience

Postgraduate, Research & Scholarly

Pages

608

Series

Wiley Classics Library

Dimensions

152x229x38

ISBN-13

9780471574286

Product ID

2082675

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