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Theory of Probability (Oxford Classic Texts in the Physical Sciences) 3rd Edition

4.0 out of 5 stars 4 customer reviews
ISBN-13: 978-0198503682
ISBN-10: 0198503687
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Editorial Reviews

Review


"This is a volume in the series Oxford Classic Texts in the Physical Sciences and is a reprint of the third, 1961 edition of the treatise first published in 1939, when it was years ahead of its time. It was the first text to develop a fundamental theory of inference based on the ideas of Bayesian statistics, ideas which have y now been generally accepted, as well as significantly developed and extended."--Quarterly of Applied Mathematics


About the Author

Jeffreys-Cambridge University
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Product Details

  • Series: Oxford Classic Texts in the Physical Sciences
  • Paperback: 470 pages
  • Publisher: Oxford University Press; 3 edition (November 12, 1998)
  • Language: English
  • ISBN-10: 0198503687
  • ISBN-13: 978-0198503682
  • Product Dimensions: 6.1 x 1.1 x 9.1 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #1,007,457 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
This is the classic book on Bayesian probability. When Jeffreys wrote it, Bayes's approach was not well known or appreciated. Jeffreys changed all that, and this is the book that did it. It is not for the faint hearted, but then what discipline-changing book is? Jeffreys was a major geophysicist, who, unfortunately failed to appreciate Wegener's continental drift (plate tectonics) hypothesis. This book will remain his legacy for many decades. One colleague commented recently, "I have written five books, and none of them is in print while Jeffreys' book is still in print nearly eighty years after he wrote it."
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Format: Paperback
If you are looking for a textbook you can use to learn statistical methods, this is not the one. The book is most useful for scientists experienced in applying the methods of statistics, who want to sharpen their mathematical apparatus to put their research on a firm foundation. The level of mathematical knowledge required to read the book is not very high but quite demanding as in many cases lots of intermediary calculations are left to the reader, so to properly read the book you have to have a pen and paper to follow the derivation of formulae.
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Format: Paperback
Jeffreys(J)does an excellent job in laying down a foundation for statistical inference based on a logical theory of probability.However,(J)appears not to have carefully read Keynes's A Treatise on Probability(1921),especially chapters 8,29,30,31 and 32.J appears not to have understood the generality of Keynes's approach.In the physical and life sciences,where one is dealing with evidence which is homogeneous and where every particle,electron,cell,molecule,gene or chromesome,etc.,is identical or practically identical to every other particle,electron,etc.,the only relevant evidence is statistical or frequency evidence.In such cases,Keynes's logical approach will give the same answer as Jeffreys would give.Keynes gave two other useful suggestions that were overlooked by J.The first was that the data pass a Lexis Q test for stability(satisfy the law of large numbers strictly).The second was Keynes's recommendation about using the Chebyshev Inequality as a lower bound on statistical estimates if the required assumptions necessary to assume a normal probability distribution were not met.J never understood that the very general axiomatic foundation that Keynes laid out in Chapter 12 of the TP applied to both precise and imprecise(partially ordered )probabilities.Keynes never claimed that the probabilities of scientific endeavor were partially ordered.Keynes did recognize,however, that the probabilities of the social sciences,liberal arts,economics,business,education and every day practical decision making were,in general,partially ordered.Read more ›
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Format: Paperback
I think bayesian theory will be used inevery fields of our life in the future.
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