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Data Analysis : A Bayesian Tutorial

Data Analysis : A Bayesian Tutorial

Data Analysis : A Bayesian Tutorial
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Data Analysis : A Bayesian Tutorial Hardback - 2006 - 2nd Edition

by Sivia, Devinderjit, Skilling, John

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Oxford University Press, Incorporated. Used - Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Details

  • Title Data Analysis : A Bayesian Tutorial
  • Author Sivia, Devinderjit, Skilling, John
  • Binding Hardback
  • Edition number 2nd
  • Edition 2
  • Condition Used - Good
  • Pages 260
  • Volumes 1
  • Language ENG
  • Publisher Oxford University Press, Incorporated
  • Publication date July 3, 2006
  • Illustrated Yes
  • Bookseller's Inventory # 56659878-20
  • ISBN 9780198568315 / 0198568312
  • Weight 1.2 lbs (0.54 kg)
  • Dimensions 9.21 x 6.14 x 0.63 in (23.39 x 15.60 x 1.60 cm)
  • Category Mathematics
  • Library of Congress subjects Bayesian statistical decision theory, Maximum entropy method
  • Library of Congress Catalogue Number 2006284782
  • Dewey Decimal Code 519.542
  • Quantity available 1

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Reader reviews for Data Analysis : A Bayesian Tutorial

From the publisher

Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.

This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design.

The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.

About the author

Devinderjit Singh Sivia
Rutherford Appleton Laboratory
Chilton
Oxon
OX11 5DJ John Skilling
Maximum Entropy Data Consultants
42 Southgate Street
Bury St Edmonds
Suffolk
IP33 2AZ
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