Jeffreys' Theory of Probability, first published in 1939, was the first attempt to develop a fundamental theory of scientific inference based on Bayesian statistics. His ideas were well ahead of their time and it is only in the past ten years that the subject of Bayes' factors has been significantly developed and extended. Recent work has made Bayesian statistics an essential subject for graduate students and researchers. This seminal book is their starting point.
 |
| ||||||||||||||||||||||||
Shop the Amazon.com Textbooks Store and save up to 70% on textbook rentals, 90% on used textbooks and 60% on eTextbooks. |
Book Description
Frequently Bought Together
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
Sir Harold Jeffreys is at University of Cambridge.
Product Details
Would you like to update product info or give feedback on images? |
More About the Author
Discover books, learn about writers, read author blogs, and more.
Customer Reviews
Share your thoughts with other customers
Most Helpful Customer Reviews
6 of 18 people found the following review helpful
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.
7 of 27 people found the following review helpful
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.Finally ,J's claim ,in his introduction ,that Keynes withdrew his claim that most probabilities are inexact and indefinite,requiring two real numbers to specify the probability relation instead of one,in a 1931 New Statesman and Nation article reviewing Ramsey's collected essays,does not have a shred of evidence to support it.This type of offhand comment makes no sense as it would require Keynes to give up his general logical theory of probability in order to accept Ramsey's very special and narrow theory of probability.
3 of 39 people found the following review helpful
By Wei Qiu
Format:Paperback
I think bayesian theory will be used inevery fields of our life in the future.
Citations (learn more)
This book cites 13
books:
See all 13 books this book cites
100
books
cite this book:
See all 100 books citing this book
- Methods of Mathematical Physics (Cambridge Mathematical Library) by Harold Jeffreys on 6 pages
- The Grammar of Science (Phoenix Edition) by Karl Pearson on 4 pages
- The Design of Experiments by Ronald A. Fisher on page 333
- A Treatise on Probability (Dover Books on Mathematics) by John Maynard Keynes on page 25
- Alice in Wonderland (Random House Pictureback) by Lori Haskins on page 245
See all 13 books this book cites
- Interpreting Probability: Controversies and Developments in the Early Twentieth Century (Cambridge Studies in Probability, Induction and Decision Theory) by David Howie on 10 pages
- Symmetry and its Discontents: Essays on the History of Inductive Probability (Cambridge Studies in Probability, Induction and Decision Theory) by S. L. Zabell on 7 pages
- Simplicity, Inference and Modelling: Keeping it Sophisticatedly Simple by Arnold Zellner on 6 pages
- Analysis of Variance for Random Models: Volume I: Balanced Data Theory, Methods, Applications and Data Analysis by Hardeo Sahai on 5 pages
- Foundations of Bayesianism (Applied Logic Series) by D. Corfield on 4 pages
See all 100 books citing this book
Books on Related Topics
(learn more)
|
What Other Items Do Customers Buy After Viewing This Item?
Sell a Digital Version of This Book in the Kindle Store
If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store.
Learn more
