Data Analysis: A Bayesian Tutorial
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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'.

  • TitleData Analysis: A Bayesian Tutorial
  • BrandOXFORD UNIVERSITY PRESS
  • ManufacturerOxford University Press
  • BindingPaperback
  • ProductGroupBook
  • ItemPartNumber20885030
  • ReleaseDate2006-07-27T00:00:01Z
  • UnitCount1
  • UPCs000198568320
  • EANs9780198568322