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Data Analysis: A Bayesian Tutorial
Devinderjit Sivia; John Skilling (Author)
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Oxford University Press
· Paperback
Data Analysis: A Bayesian Tutorial - Devinderjit Sivia; John Skilling
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Synopsis "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 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'.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
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