

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 (version 3.5) 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.
Download Chapter 1 (below) for examples.
Sebtel Press, 2013.
ISBN 9780956372840.
Available from:
Ebook available from:

Sebtel Press, 2015.
ISBN 9780993367908.
Available from:
These books contain identical text, but "Bayes' Rule With MatLab" and "Bayes' Rule With Python (version 3.5)" include code snippets, which reproduce key figures and numerical results.
Download Chapter 1 (above) for examples.

Sebtel Press, 2016.
ISBN 9780993367939.
Available from:

Sebtel Press, 2016.
ISBN 9780993367946.
Available from:

