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 common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation. As an aid to understanding, online computer code (in MatLab, Python and R) reproduces key numerical results and diagrams. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis.
The books below contain identical text, but "Bayes' Rule With MatLab", "Bayes' Rule With Python (version 3.5)" and "Bayes' Rule With R" include code snippets, which reproduce key figures and numerical results. Download Chapter 1 (below) for examples.

       

Available as ebook (from Amazon and Selz), paperback and hardback.
 

Sebtel Press, 2013.
ISBN 9780956372840,
ISBN 9780956372895
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Ebook available from Selz, a trustworthy site:

Bayes Rules - Ebook from Selz

Sebtel Press, 2015.
ISBN 978-0993367908.

Available from:

   

Ebook available from Selz, a trustworthy site:

Bayes Rules - Ebook from Selz

Sebtel Press, 2016.
ISBN 978-0993367939.

Available from:

   

Ebook available from Selz, a trustworthy site:

Bayes Rules - Ebook from Selz

Sebtel Press, 2016.
ISBN 978-0993367946.

Available from:

   

Ebook available from Selz, a trustworthy site:

Bayes Rules - Ebook from Selz