Category: Science & Geography|
The author of the book: Devinderjit Sivia
Format files: PDF, EPUB, TXT, DOCX
The size of the: 680 KB
Edition: Oxford University Press
Date of issue: 27 July 2006
Description of the book "Data Analysis: A Bayesian Tutorial":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 PDF 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 ePub 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.
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