Data Analysis: A Bayesian Tutorial

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Clarendon Press, 1996 - Science - 189 pages
2 Reviews
Statistics lectures have often been viewed with trepidation by engineering and science students taking an ancillary course in this subject. Whereas there are many texts showing "how" statistical methods are applied, few provide a clear explanation for non-statisticians of how the principlesof data analysis can be based on probability theory. Data Analysis: A Bayesian Tutorial provides such a text, putting emphasis as much on understanding "why" and "when" certain statistical procedures should be used as "how". This difference in approach makes the text ideal as a tutorial guide forsenior 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. With its central emphasis on a fewfundamental rules, this book takes the mystery out of statistics by providing a clear rationale for some of the most widely-used procedures.

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User Review  - PDExperiment626 - LibraryThing

This book not only is a good book to learn Bayesian statistics from, but it's also a great reference for the subject as well. Taking a very hands-on approach, the concepts and philosophy of Bayesian ... Read full review

User Review - Flag as inappropriate

Good, but too short. Does not cover computational methods.


The basics
Parameter estimation II
Model selection
Assigning probabilities
Nonparametric estimation
Experimental design
Gaussian integrals and related topics

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About the author (1996)

D. S. Sivia, Rutherford Appleton Laboratory and St Catherine's College, Oxford.

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