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The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Paperback – 14 Sep 2012


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Product details

  • Paperback: 336 pages
  • Publisher: Yale University Press (14 Sep 2012)
  • Language: English
  • ISBN-10: 0300188226
  • ISBN-13: 978-0300188226
  • Product Dimensions: 2.5 x 15.9 x 23.5 cm
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (28 customer reviews)
  • Amazon Bestsellers Rank: 11,855 in Books (See Top 100 in Books)

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Review

"'An engrossing study... Her book is a compelling and entertaining fusion of history, theory and biography.' (Ian Critchley, Sunday Times) 'The Theory That Would Not Die is the first popular science book to document the rocky story of Bayes's rule. At times, her tale has everything you would expect of as modern-day thriller... To have crafted a page-turner out of the history of statistics is an impressive feat. If only lectures at university had been this racy.' (David Robson, New Scientist) 'Readers will be amazed at the impact that Bayes' rule has had in diverse fields, as well as by its rejection by too many statisticians... reading McGrayne's book has made me determined to try, once again, to master the intricacies of Bayesian statisics.' (The Lancet)"

About the Author

Sharon Bertsch McGrayne is the author of numerous books, including Nobel Prize Women in Science: Their Lives, Struggles, and Momentous Discoveries and Prometheans in the Lab: Chemistry and the Making of the Modern World. She lives in Seattle.

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46 of 46 people found the following review helpful By Mr. David Hitchin on 18 July 2011
Format: Hardcover Verified Purchase
Whether or not you will enjoy this book depends on who you are. If you enjoy reading books about popular science, and trying to solve the occasional simple mathematical or logical puzzle, then you are ready for this one. If you want to understand the theory in any depth, or use it to solve problems, then you will need at least first-year undergraduate statistics to get started, much more to make progress -­ and a book with the formal mathematics, but begin with this one first to get a perspective on the field before going into detail.

It is not obvious how you should use data to decide what to believe or how to act, and, as theories of statistics were developed, statisticians tried several different ways of thinking about data and the conclusions that could reasonably be drawn from them. Unfortunately the divisions of opinion (perhaps largely due to the personalities of the leading thinkers) resulted in acrimonious and inconclusive arguments.

Thomas Bayes was a clergyman who died in 1761, leaving behind some mathematical papers. One of these was revised and corrected by Richard Price, so we don't know quite what Bayes wrote or what he meant. This paper was the origin of two things: (1) the widely-used and uncontroversial `Bayes Theorem', and (2) the controversial idea that probability could be expressed in terms of a measure of belief. In Bayesian statistics the researcher puts a belief into numerical terms and refines this belief in the light of subsequently observed data. The 'subjective' aspect of the theory brought it into disrepute, where it lingered for nearly 200 years. Many people faced with practical problems found that Bayesian methods worked, but either they didn't know about Bayes or they preferred not to invite criticism by mentioning his name.
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11 of 11 people found the following review helpful By Paul Bowes TOP 500 REVIEWER on 17 Nov 2011
Format: Hardcover
This is an excellent history of the development and application of Bayes' Theorem. Intended for the general reader with an interest in probability and the history of science, it is clearly written with a minimum of mathematics, and covers the ground efficiently.

It is particularly interesting for what it reveals of the way in which new ideas become part of intellectual discourse; in this case, by enduring a long period of suspicion and neglect before being rescued by the enthusiasm of practitioners rather than theorists. McGrayne offers many sidelights on the clandestine uses made of Bayes by the military and the intelligence community, which go some way to explaining why the power of these techniques was so long in receiving acknowledgement. The powerful personalities of the people involved receive extensive attention: no reader will come away from this book in ignorance of the degree to which accidents of institutional history and personal character condition the intellectual environment. Recommended.
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19 of 20 people found the following review helpful By egmont on 19 Jan 2012
Format: Hardcover
This is half a book and the half is very good - it would be worth 5 stars. You learn about the fascinating people who deployed Bayesian inference, particularly the Enigma codebreakers; about the statisticians who thought it was a complete waste of time; about the quirks of history which made people so slow to recognize its value.

All very good. But this is a book about some mathematics, and there is very little maths! Bayes' rule gets an equation, but that's not actually Bayesian inference. The author keeps saying that sometimes frequentists and Bayesians get the same results, but no example. And sometimes very different results, but no example. Bayes himself seems to have proved it, but no details on the proof. Some other people seem to have proved it, but ditto. Bayesian calculations are said to be very difficult pre-computer and pre-MCMC, but no example so you can see why it's such a problem.

So: a little disappointing - but maybe it does provide the questions you can type into Google after this book has not provided the answers.
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7 of 7 people found the following review helpful By David on 11 Dec 2012
Format: Paperback Verified Purchase
I have to agree with the other reviewers who were disappointed by the lack of mathematics in this book. To borrow an old cliche, Bayes without the mathematics is Hamlet without the prince. It is certainly interesting to read about the academic squabbles, the logical breakthroughs, the military applications, and so on; but I want to know HOW (for instance) Turing used Bayes to decode Enigma, not merely THAT he used Bayes. I wonder just how many readers would pick up the book if they didn't already have some understanding of what Bayes was about; but if McGrayne were worried about the ability of her readers to follow a mathematical explanation then all she needed to do was relegate the detailed explanations to appendices. She deserves credit for the appendix on mammograms and breast cancer, which is admirably simple, but as far as I can see that is the only point at which even the algebraic statement of the familiar theorem appears.

I first came across the Bayesian approach to statistics as a graduate student in 1970 (thanks to Tribus' "Rational Descriptions, Decisions and Designs" - pity he didn't get a name check from McGrayne) and, like Saul on the road to Damascus, I underwent something like a religious conversion. Unlike St Paul, I never suffered any persecution in consequence, but it is good to see that what seemed to me at the time a fringe religion has now achieved something approaching statistical orthodoxy. For that reassurance, I thank Ms McGrayne.
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