- 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: 4.8 out of 5 stars See all reviews (35 customer reviews)
- Amazon Best Sellers Rank: #54,052 in Books (See Top 100 in Books)
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Probability Theory: The Logic of Science 1st Edition
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Top Customer Reviews
If you deal at all with probability theory, statistics, data analysis, pattern recognition, automated diagnosis -- in short, any form of reasoning from inconclusive or uncertain information -- you need to read this book. It will give you new perspectives on these problems.
The downside to the book is that Jaynes died before he had a chance to finish it, and the editor, although capable and qualified to fill in the missing pieces, was understandably unwilling to inject himself into Jaynes's book. One result is that the quality of exposition suffers in some of the later chapters; furthermore, the author is not in a position to issue errata to correct various minor errors. Volunteer efforts are underway to remedy these problems -- those who buy the book may want to visit the "Unofficial Errata and Commentary" website for it, or check out the etjaynesstudy mailing list at Yahoo groups.
If you work in any field where on needs to "reason with incomplete information" this book is invaluable.
As others have already mentioned, Jaynes never finished this book. The editor decided to "fill in" the missing parts by putting excercises that, when finished by the reader, provide what (so the editor guesses) Jaynes left out. I find this solution a bit disappointing. The excercises don't take away the impression that holes are left in the text. It would have been better if the editor had written the missing parts and then printed those in different font so as to indicate that these parts were not written by Jaynes. Better still would have been if the editor had invited researchers that are intimately familiar with Jaynes' work and the topic of each of the missing pieces to submit text for the missing pieces.Read more ›
Jaynes' knowledge of the history and philosophy of statistics is far deeper than that of most statisticians (including myself). His trenchant style gives the book a narrative drive and cover-to-cover readability that, in my experience, is unique in the field. One such strand is the continual battle between his respect for RA Fisher's abilities, and his exasperation at how wrongheadedly he feels they were channelled. And he doesn't hesitate to take on philosophical heavyweights such as Hume in defending the possibility - - in fact, the necessity - - of inductive inference. However, this style also produces some more bitter fruit, such as the way the author repeatedly likens himself to historical victims of religious persecution.
The book weakens when it turns to applications. Regression with errors in both variables is said to be 'the most common problem of inference faced by experimental scientists' who have 'searched the statistical literature in vain for help on this'. Good points. So why don't the author and editor give us at least a reference for just one of the 'correct solutions' which 'adapt effortlessly' to scientists' needs? And Jaynes' argument that the null hypothesis procedure 'saws off its own limb' would also rule out mathematical proof by reductio ad absurdum.
When estimating periodicities, we're told that 'the eyeball is a more reliable indicator of an effect than an orthodox equal-tails test'.Read more ›
Most Recent Customer Reviews
I came to this book after coming from a frequentest education in the mid 1990's in research statistics. Read morePublished 1 day ago by Philip Leitch
This is a classic - perhaps THE classic exposition of Bayesian statistics for physical scientists. Among other things, Jaynes strove to rediscover and rehabilitate Sir Harold... Read morePublished 3 months ago by SDS Brooklyn
I really think everyone should read this book, and R. T. Cox's book. This books make plain the philosophical and mathematical reasons that all statistics should be Bayesian. Read morePublished 4 months ago by W. Sturgis
If you ever thought hypothesis testing, p-values, etc. (as taught in most undergraduate courses) was "hokey," this book will validate your perceptions. Read morePublished 7 months ago by brethvoice
Finally have purchased this book. I feel a need these days to find an indisputable means to defend my opinions about almost everything. Read morePublished 16 months ago by cheryl
The book is a sweeping, albeit unfinished, treatise on probability theory. Part of it covers what would make textbook material on probability theory and its applications - how to... Read morePublished 18 months ago by mathiou
Luckily, I found out this book after reading Keynes' probability book. This is not an elementary book for beginners, though math is not complicated inside. Read morePublished on December 31, 2013 by white rabbit