- Hardcover: 753 pages
- Publisher: Cambridge University Press; 1 edition (June 9, 2003)
- Language: English
- ISBN-10: 0521592712
- ISBN-13: 978-0521592710
- Product Dimensions: 6.8 x 1.5 x 9.7 inches
- Shipping Weight: 3.5 pounds (View shipping rates and policies)
- Average Customer Review: 41 customer reviews
- Amazon Best Sellers Rank: #45,256 in Books (See Top 100 in Books)
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Probability Theory: The Logic of Science 1st Edition
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"...tantalizing ideas...one of the most useful and least familiar applications of Bayesian theory...Probability Theory [is] considerably more entertaining reading than the average statistics textbook...the conceptual points that underlie his attacks are often right on."
"This is a work written by a scientist for scientists. As such it is to be welcomed. The reader will certainly find things with which he disagrees, but he will also find much that will cause him to think deeply not only on his usual practice by also on statistics and probability in general. Probability Theory: the Logic of Science is, for both statisticians and scientists, more than just 'recommended reading': it should be prescribed."
"...the rewards of reading Probability Theory can be immense."
Physics Today, Ralph Baierlein
This is not an ordinary text. It is an unabashed, hard sell of the Bayesian approach to statistics. It is wonderfully down to earth, with hundreds of telling examples. Everyone who is interested in the problems or applications of statistics should have a serious look.
"[T]he author thinks for himself...and writes in a lively way about all sorts of things. It is worth dipping into it if only for vivid expressions of opinion...There are many books on Bayesian statistics, but few with this much color."
Notices of the AMS
Going beyond the conventional mathematics of probability theory, this study views the subject in a wider context. It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.
Top customer reviews
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It is true Jaynes' style is caustic against positions that are contrary to his owns. But he is very convincing on the reasons he gives to pinpoint the big holes in the so called "orthodox" school of probability and statistics.
Besides, the book is very lengthy, without being prolix, on its explanations, making it very pedagogical. Constrasting with that, nevertheless, Jaynes sometimes proposes examples that I believe only a mathematician or physicist with specific knowledge of the subject mentioned by the author will be able to follow. But those parts do not impact understanding of the main ideas.
It must be noted also that "Probaility theory: the logic of science" is mainly a theory book. Its goal is to present probability as an extension of deductive logic. It only brings a small number of exercises.
The best thing about this book, at least for me, is having a style that really makes me look forward reading the next page, something very rare for a technical book. In fact, the only other book I came across that had that virtue was the "Feynman Lectures on Physics".
In my opinion, this book is a required read for anyone who wishes to understand precisely how the scientific worldview is, in a mathematically defensible sense, the best possible worldview, the one that lets us optimally use evidence to develop an interlocked Bayesian network of evidence supported beliefs that can change and evolve as the evidence is accumulated. It also shows the critical connections between physics and statistical mechanics and Shannon's theorem in computational information theory, laying the foundation for a fair bit of modern physics as it demonstrates that physical entropy and information entropy are very much one and the same thing, from a certain point of view.