A Bayesian Tutorial 2nd Revised edition
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Data Analysis by Devinderjit Sivia
Book DescriptionStatistics 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'. Features * An easy to read tutorial introduction to data anlaysis. * Concise, being one of the slimmest books in the field! * Self-contained--assumes little or no previous statistical training. * Good illustrative examples where the basic concepts are explained with a series of examples that become progressively more advanced, but that are always kept as simple as possible to aid understanding. * A contribution from John Skilling, an expert in numerical techniques. He introduces the simple but powerful new 'nested sampling' technique for Bayesian computiaton.
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Book DetailsISBN: 9780198568322
(233mm x 159mm x 15mm)
Imprint: Oxford University Press
Publisher: Oxford University Press
Publish Date: 1-Jun-2006
Country of Publication: United Kingdom
Books By Author Devinderjit Sivia
Data Analysis, Hardback (June 2006)» View all books by Devinderjit Sivia
Focuses on Bayesian methods and maximum entropy, aimed at senior undergraduates in science and engineering. This book shows how a few fundamental rules can be used to tackle a variety of problems in data anlysis. Topics covered include reliability analysis, multivariate optimisation, least-squares and maximum likelihood, and more.
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Author Biography - Devinderjit Sivia
John Skilling Maximum Entropy Data Consultants 42 Southgate Street Bury St Edmonds Suffolk IP33 2AZ
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