Data Analysis : A Bayesian Tutorial Paperback / softback
Paperback / softback
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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 experimentaldesign. 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'.
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- Format:Paperback / softback
- Pages:264 pages, 68 line drawings + 1 halftone
- Publisher:Oxford University Press
- Publication Date:01/06/2006