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Synopsis
Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. Bayes' rule is derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and online Python programs provided. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis.
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Review
"A crackingly clear tutorial for beginners. Exactly the sort of book required for those taking their first steps in Bayesian analysis." Dr Paul A. Warren. School of Psychological Sciences, University of Manchester. "This book is short and eminently readable. It introduces the Bayesian approach to addressing statistical issues without using any advanced mathematics, which should make it accessible to students from a wide range of backgrounds, including biological and social sciences." Dr Devinder Sivia. Lecturer in Mathematics, St John's College, Oxford University, and author of Data Analysis: A Bayesian Tutorial. "For those with a limited mathematical background, Stone's book provides an ideal introduction to the main concepts of Bayesian analysis. " Dr Peter M Lee. Department of Mathematics, University of York. Author of Bayesian Statistics: An Introduction. "Bayesian analysis involves concepts which can be hard for the uninitiated to grasp. Stone's patient pedagogy and gentle examples convey these concepts with uncommon lucidity. " Dr Charles Fox. Department of Computer Science, University of Sheffield.
About the Author
Dr James Stone is a Reader in Vision and Computational Neuroscience at the University of Sheffield, England.
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- PublisherSebtel Press
- Publication date2013
- ISBN 10 0956372848
- ISBN 13 9780956372840
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages180
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