- 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: 40 customer reviews
- Amazon Best Sellers Rank: #90,041 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.
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It wasn't until this year when I have borrowed, and will shortly purchase this book: "Probability Theory: The Logic of Science" by the late E.T. Jaynes ISBN 10: 0521592712 ISBN 13: / 9780521592710. This single book has changed my perspective and not only made my understanding of probability more complete, but it has made me a better practitioner, producing better and more accurate results.
I would heartily recommend this book for the theoretical reasoning behind Bayesian statistics and better, and more accessible understanding and usage. This is a far superior book for the Bayesian novice of MY level, and made most other statistics texts more accessible. It provided an overlaying logic, a philosophical approach defining the basis of the approach, the reasons why the author takes the approach throughout the book, and multiple examples of contractions from other authors and the author's views of those contradictions. In short - it is an accessible book to students and novices.
I have ready many books, on Bayesian statistics and this books is NOT a Bayesian text (probably approaching 50 in total). This book differs in that it combines the theory of Frequentests and Bayesians with an overlay of Logic. It truly is a practical "Probability Theory". I still have, and cherish, my Parametric, Non-Parametric statistics, and Bayesian texts, but now I can get more information use use out of them by a well theorised and practical implementation.
The sadly late E. T. Jaynes has a unique way of explaining pragmatic logic underlying approaches that neither invalidates either side of the statistics debate and increases the accessibility of statistics. Jaynes is to probability what Gladwess is to psychology and anthropology.
I doubt this book will ever age as the logic and advice is sage.
The book is quite entertaining, and very enlightening for anyone interested in the history of how statistics came to be taught the way it is today, with measure theory, sample spaces, random variables, etc. and all of the troubles they cause. Fortunately, this vastly more general theory also disposes efficiently of all paradoxes created by attempting to apply the special cases of Kolmogorov probability to many common scientific problems.
I specifically recommend this to anyone who thinks ``scientists'' as a whole agree on the scientific method and what constitutes "valid" inference. Some scientists do not even believe inference can be valid, and among those who do, there is vast disagreement on what a valid inference is.
This book argues that probability and statistics should stick together as foundamental tools for knowledge discovery and Bayesian framework is the only logically consistent way to approach incomplete information problems. The book covers historical background of modern probability and statistics theories, as the age of the author prolongs through the prosperous research period after the second world war.
The author takes sharp critics on frequentists' approach, which is taught in the main stream. The author shows both frequentist and Bayesian approaches agree with each other if the problem is nice (e.g., existence of sufficient statistics), but the latter has an edge in general.
Overall, the book is very informative and contains many enlightening points.
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".