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OverviewStatistics 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'. Full Product DetailsAuthor: Devinderjit Sivia (Rutherford Appleton Laboratory and St Catherine's College, Oxford) , John Skilling (Maximum Entropy Data Consultants)Publisher: Oxford University Press Imprint: Oxford University Press Edition: 2nd Revised edition Dimensions: Width: 16.10cm , Height: 2.00cm , Length: 24.10cm Weight: 0.529kg ISBN: 9780198568315ISBN 10: 0198568312 Pages: 260 Publication Date: 01 June 2006 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: To order  Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us. Table of Contents1: Sivia: The Basics 2: Sivia: Parameter Estimation I 3: Sivia: Parameter Estimation II 4: Sivia: Model Selection 5: Sivia: Assigning Probabilities 6: Sivia: Non-parametric Estimation 7: Sivia: Experimental Design 8: Sivia: Least-Squares Extensions 9: Skilling: Nested Sampling 10: Skilling: Quantification Appendices BibliographyReviewsOne of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. Katie St. Clair MAA Reviews One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. * Katie St. Clair MAA Reviews * `Review from previous edition Providing a clear rationale for some of the most widely used procedures.' European Journal of Engineering Education `This small (less than 200 pages) but much-needed book contains a wealth of worked-out numerical examples of Bayesian treatments of data, expounded from a theoretical standpoint identical to ours. It should be considered an adjunct to the present work, supplying a great deal of practical advice for the beginner, at an elementary level that will be grasped readily by every science or engineering student. ' Ed Jaynes in 'Probability Theory: The Logic of Science', CUP 2003 Author InformationDevinderjit Singh Sivia Rutherford Appleton Laboratory Chilton Oxon OX11 5DJ John Skilling Maximum Entropy Data Consultants 42 Southgate Street Bury St Edmonds Suffolk IP33 2AZ Tab Content 6Author Website:Countries AvailableAll regions |
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