Bayes' Rule: A Tutorial Introd

James V Stone

ISBN 10: 0956372848 / ISBN 13: 9780956372840

Published by Sebtel Press, 2013

About this Item

Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Seller Inventory # 00089754335

Bibliographic Details

• Title: Bayes' Rule: A Tutorial Introd
• Publisher: Sebtel Press
• Publication Date: 2013
• Language: English
• ISBN 10: 0956372848
• ISBN 13: 9780956372840
• Binding: Soft cover
• Edition: 5th or later Edition
• Condition: Good

About this title

Synopsis

What does a medical test tell us about the chances of having a particular disease?
How can we tell if a spoken phrase is, 'four candles’ or 'fork handles’?
How do we a perceive a three-dimensional world from from the two-dimensional images on our retinas?

The short answer is Bayes’ rule, which transforms meaningless statistics and raw data into useful information. Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, intuitive visual representations of real-world examples are used to show how Bayes' rule is actually a form of common sense reasoning. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to gain an intuitive understanding of Bayesian analysis. As an aid to understanding, online computer code (in MatLab, Python and R) reproduces key numerical results and diagrams.

Stone’s book is renowned for its visually engaging style of presentation, which stems from teaching Bayes’ rule to psychology students for over 10 years as a university lecturer.

From the Back Cover

"Bayes' Rule explains in a very easy to follow manner the basics of Bayesian analysis." Dr Inigo Arregui,

Ramon y Cajal Researcher, Institute of Astrophysics, Spain.

"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.