Data Analysis: A Bayesian Tutorial

By Devinderjit Singh Sivia and John Skilling

Book Overview

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'.

• Format: Paperback
• Language: English
• ISBN: 0198568320
• ISBN13: 9780198568322
• Release Date: June 2006
• Publisher: OUP UK
• Length: 264 Pages
• Weight: 0.98 lbs.
• Dimensions: 0.6" x 7.6" x 9.1"