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This title in other editions

Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers (Cambridge Series in Statistical and Probabilistic Mathematic)

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Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers (Cambridge Series in Statistical and Probabilistic Mathematic) Cover

 

Synopses & Reviews

Publisher Comments:

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unique in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many new statistical methods, not available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.

Synopsis:

Describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students as well as statistical and interdisciplinary researchers. It is unique in presenting Bayesian statistics with an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data.

Synopsis:

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. The first chapter presents a comparison with traditional Fisherian methods. Subsequent chapters relate Bayesian methods to many areas of statistics, for instance, the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.

Synopsis:

Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data.

Description:

Includes bibliographical references (p. 303-319) and indexes.

Product Details

ISBN:
9780521594172
Editor:
Gill, R.
Author:
Hsu, John S. J.
Editor:
Gill, R.
Author:
Leonard, Thomas
Author:
Ripley, B. D.
Author:
Williams, D.
Author:
Ross, S.
Author:
Gill, R.
Author:
Stein, M.
Publisher:
Cambridge University Press
Location:
Cambridge, U.K. ;
Subject:
Statistics
Subject:
Bayesian statistical decision theory
Subject:
Probability & Statistics - General
Subject:
Mathematics | Probability and Statistics
Edition Number:
1
Edition Description:
Hardback
Series:
Cambridge Series in Statistical and Probabilistic Mathematic
Series Volume:
5
Publication Date:
20110131
Binding:
Hardcover
Grade Level:
College/higher education:
Language:
English
Illustrations:
Y
Pages:
348
Dimensions:
10.36x7.36x1.00 in. 1.87 lbs.

Related Subjects

Religion » Comparative Religion » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers (Cambridge Series in Statistical and Probabilistic Mathematic) New Hardcover
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$166.50 In Stock
Product details 348 pages Cambridge University Press - English 9780521594172 Reviews:
"Synopsis" by , Describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students as well as statistical and interdisciplinary researchers. It is unique in presenting Bayesian statistics with an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data.
"Synopsis" by , This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. The first chapter presents a comparison with traditional Fisherian methods. Subsequent chapters relate Bayesian methods to many areas of statistics, for instance, the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.
"Synopsis" by , Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data.
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