Probability Theory: The Logic of Science Hardcover – Jun 9 2003
Frequently Bought Together
Customers Who Bought This Item Also Bought
No Kindle device required. Download one of the Free Kindle apps to start reading Kindle books on your smartphone, tablet, and computer.
Getting the download link through email is temporarily not available. Please check back later.
To get the free app, enter your mobile phone number.
What Other Items Do Customers Buy After Viewing This Item?
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.
This book develops probability theory from first principles as an extension of deductive logic. In deductive logic, propositions can have only three possible truth values: true, false, and irremediable uncertainty. Therefore, the goal of the book is to describe a consistent extended logic that assigns real numbers to the plausibility of propositions. The requirements for such a system are derived from five simple desiderata, which serve as the postulates of this theory - and it turns out that *any* such system is equivalent to probability theory, to within a monotonic transformation.
Probability theory is then developed through applications to problems which grow more and more complex. The author demonstrates its use in direct sampling problems and so-called inverse problems, aka Bayesian probability. He derives procedures for multiple hypothesis testing, parameter estimation, and significance testing, and shows that although there are close connections between probability and frequency of occurrence in a large number of trials, no probability is *simply* a frequency.
Following this, the author presents solutions to the problem of assigning prior probabilities, and develops decision theory as an adjunct to probability theory. The author then compares and contrasts mainstream or "orthodox" statistical theory with probability theory as extended logic, and (perhaps unsurprisingly) finds severe deficiencies in the orthodox methods. The final chapters concern even more advanced applications.
Readers should be well versed in simple calculus and multivariate calculus; some familiarity with convolution integrals and finite combinatorics is also an asset, but not essential.Read more ›
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 ›
Most recent customer reviews
it offers a mathematical discussion of probability
from the point of view of information theory. It argues
against the frequentist approach. Read more
To "pure" mathematicians, probability theory is measure theory in spaces of measure 1. To the extent to which you remain a "pure" mathematician, this book will be incomprehensible... Read morePublished on June 25 2003 by Michael Hardy
Jaynes' work on probability has inspired many students and academics over the years. Jaynes advocates probability as a degree of belief. Read morePublished on June 17 2003 by Ali Abbas
Look for similar items by category
- Books > Professional & Technical > Professional Science > Mathematics > Applied
- Books > Professional & Technical > Professional Science > Mathematics > Mathematical Physics
- Books > Qualifying Textbooks - Fall 2007 > Science
- Books > Science & Math > Mathematics > Applied > Probability & Statistics
- Books > Science & Math > Mathematics > Mathematical Physics
- Books > Science & Math > Physics
- Books > Textbooks > Sciences > Mathematics > Statistics
- Books > Textbooks > Sciences > Physics