14th out of 14 books — 11 voters
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Data Analysis: A Bayesian Tutorial
Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basi ...more
Paperback, 246 pages
Published July 1st 2006 by Oxford University Press, USA
(first published September 26th 1996)
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Oct 07, 2010 Elliptic Blue rated it really liked it
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 statistical analysis are clearly presented through lucid explanations and an abundance of well-chosen examples. In the second edition, there is also a significant portion of the book dedicated to algorithmic implementation of Bayesian inference schemes; and this material is accompanied by C source co ...more
I'm afraid I only got about half way through this, and will return to it once I've brushed up on my vector calculus, as some of the maths was *very* unfamiliar to me (I suspect it's written with experimental scientists with a background in physics or engineering in mind, rather than compsci geeks). Despite that though, I think I managed to absorb a lot of the principles of and the rationale behind the bayesian approach to statistical analysis, and I look forward to understanding the detail once ...more
I enjoyed the first few chapters of this book. They were a good introduction to Baysian inference even if you don't know much about statistics. Unfortunately this fall to this fell to the bottom of my priority list and I took so long reading the rest of it that I didn't get anything out of it our really follow it. My fault not the author's.
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