Data Analysis - A Bayesian Tutorial (Hardcover, 2nd Revised edition)

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'.

General

Imprint:	Oxford UniversityPress
Country of origin:	United Kingdom
Release date:	June 2006
First published:	July 2006
Authors:	Devinderjit Sivia • John Skilling
Dimensions:	241 x 161 x 20mm (L x W x T)
Format:	Hardcover
Pages:	260
Edition:	2nd Revised edition
ISBN-13:	978-0-19-856831-5
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics
LSN:	0-19-856831-2
Barcode:	9780198568315

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