Data Analysis : A Bayesian Tutorial Paperback
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'.
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.
- Format: Paperback
- Pages: 264 pages, 68 line drawings + 1 halftone
- Publisher: Oxford University Press
- Publication Date: 01/06/2006
- Category: Probability & statistics
- ISBN: 9780198568322