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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


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

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    Available in PDF Format | The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from.pdf | English
    Sharon Bertsch Mcgrayne(Author)
Bayes' rule appears to be a straightforward, one-line theorem:by updating our initial beliefs with objective new information, we get anew and improved belief. To its adherents, it is an elegant statementabout learning from experience. To its opponents, it is subjectivity runamok.In the first-ever account of Bayes' rule for generalreaders, Sharon Bertsch McGrayne explores this controversial theorem andthe human obsessions surrounding it. She traces its discovery by anamateur mathematician in the 1740s through its development into roughlyits modern form by French scientist Pierre Simon Laplace. She revealswhy respected statisticians rendered it professionally taboo for 150years-at the same time that practitioners relied on it to solve crisesinvolving great uncertainty and scanty information (Alan Turing's rolein breaking Germany's Enigma code during World War II), and explains howthe advent of off-the-shelf computer technology in the 1980s proved tobe a game-changer. Today, Bayes' rule is used everywhere from DNAde-coding to Homeland Security. Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

"A masterfully researched tale of human struggle and accomplishment . . . . Renders perplexing mathematical debates digestible and vivid for even the most lay of audiences."--Michael Washburn, "Boston Globe"--Michael Washburn "Boston Globe ""[An] engrossing study....Her book is a compelling and entertaining fusion of history, theory and biography."--Ian Critchley, "Sunday Times"--Ian Critchley"Sunday Times" (06/19/2011)"Well known in statistical circles, Bayes's Theorem was first given in a posthumous paper by the English clergyman Thomas Bayes in the mid-eighteenth century. McGrayne provides a fascinating account of the modern use of this result in matters as diverse as cryptography, assurance, the investigation of the connection between smoking and cancer, RAND, the identification of the author of certain papers in The Federalist, election forecasting and the search for a missing H-bomb. The general reader will enjoy her easy style and the way in which she has successfully illustrated the use of a result of prime importance in scientific work."-- Andrew I. Dale, author of "A History of Inverse Probability From Thomas Bayes to Karl Pearson" and "Most Honorable Remembrance: The Life and Work of Thomas Bayes"--Andrew I. Dale (08/19/2010)"A book simply highlighting the astonishing 200 year controversy over Bayesian analysis would have been highly welcome. This book does so much more, however, uncovering the almost secret role of Bayesian analysis in a stunning series of the most important developments of the twentieth century. What a revelation and what a delightful read!"--James Berger, Arts & Sciences Professor of Statistics, Duke University, and member, National Academy of Sciences--James Berger (08/16/2010)"We now know how to think rationally about our uncertain world. This book describes in vivid prose, accessible to the lay person, the development of Bayes' rule over more than two hundred years from an idea to its widespread acceptance in practice." --Dennis Lindley, University College London--Dennis Lindley (08/09/2010)""The Theory That Would Not Die" is a rollicking tale of the triumph of a powerful mathematical tool."--Andrew Robinson, "Nature"--Andrew Robinson"Nature" (07/28/2011)"Compelling, fast-paced reading full of lively characters and anecdotes. . . .A great story." --Robert E. Kass, Carnegie Mellon University--Robert E. Kass"A very compelling documented account. . .very interesting reading."--Jose Bernardo, "Valencia List Blog"--Jose Bernardo "Valencia List Blog """The Theory That Would Not Die" is an impressively researched, rollicking tale of the triumph of a powerful mathematical tool."--Andrew Robinson, "Nature Vol. 475"--Andrew Robinson"Nature Vol. 475" (07/28/2011)"An intellectual romp touching on, among other topics, military ingenuity, the origins of modern epidemiology, and the theological foundation of modern mathematics."--Michael Washburn, "Boston Globe"--Michael Wasburn "Boston Globe "."....scientists and statisticians have fought over a deep philosophical divide about probability, which Sharon Bertsch McGrayne explores with great clarity and wit."--Christine Evans-Pughe, "Engineering and Technology Magazine"--Christine Evans-Pughe"Engineering and Technology Magazine" (11/01/2011)"Thorough research of the subject matter coupled with flowing prose, an impressive set of interviews with Bayesian statisticians, and an extremely engaging style in telling the personal stories of the few nonconformist heroes of the Bayesian school."--Sam Behseta, "Chance"--Sam Behseta "Chance ""For the student who is being exposed to Bayesian statistics for the first time, McGrayne's book provides a wealth of illustrations to whet his or her appetite for more. It will broaden and deepen the field of reference of the more expert statistician, and the general reader will find an understandable, well-written, and fascinating account of a scientific field of great importance today."--Andrew I./i>--Andrew I. Dale "Notices of the American Mathematical Society """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 a 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"--David Robson"New Scientist" (07/02/2011)"A very engaging book that statisticians, probabilists, and history buffs in the mathematical sciences should enjoy."--David Agard, "CryptologIA"--David Agard "CryptologIA ""Fascinating....I truly admire [McGrayne's] style of writing, and ... ability to turn complex mathematical ideas into intriguing stories, centered around real people."--Judea Pearl, winner of the 2012 Turing Award--Judea Pearl"Delightful ... [and] McGrayne gives a superb synopsis of the fundamental development of probability and statistics by Laplace."--Scott L./i> --Physics Today "Scott L. Zeger "

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  • By David Hitchin on 18 July 2011

    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.In the last 60 years or so there has been a big revival in interest in Bayes theory, and it has been used to solve many problems that weren't amenable to traditional methods. The big barrier was that some of the methods needed huge calculations, but with the availability of cheap, fast computers and new methods of calculation that barrier has almost disappeared.Sharon Bertsch Mcgrayne's book gives a very clear and thorough history of "the theory that would not die." As a practising statistician for more than 40 years I knew much of the published work that she has written about, and can vouch for her accuracy (there are a few corrections on her website), but until I read this book I did not have a clear idea of all of the historical developments and controversies. My only criticism is that the bibliography is organised by chapters, rather than as one alphabetically ordered sequence.

  • By Conall Boyle on 23 June 2013

    Well first off, I'm delighted to see that co-founder Richard Price of Llangeinor is given proper credit. (Llangeinor in South Wales, is near where I live, But Rev Price did much more than re-write Rev Bayes's notes)And I'm fascinated by the names of all the statisticians who I'd heard about, and a few I've even met (I taught stats at a midlands University).But having re-read it more closely, I now understand my quibbles: All Bayesians are treated as unsung heroes, the un-converted are knaves.For instance: p116 "Cornfield's identification [in the Framingham study] in 1962 of the most critical risks factors [high cholesterol, high blood pressure] for cardiovascular disease produced....a dramatic drop in death rates from c.v. diease.", because it seems that Cornfield used Bayes and the others didn't.Now this is a complete travesty! Read Gary Taubes 'The Diet Delusion' and you'll discover that poor analysis, and especially pre-conceptions meant that Framingham produced the 'wrong' results. Apart from smoking, none of the other factors matter. The low-fat obsession is making matters worse. A clear example of bad priors causing wrong posteriors?So did Cornfield and his bayesianism lead to these false conclusions? Ms. McGrayne, the author could be forgiven for not knowing this, but it shows how the book works -- run with any 'success' for bayesianism (and ignore the failures?)Her attitude to my favourite statistician, Tukey is bizarre to say the least. She claims he did all sorts of secret work both for the military and for commercial clients that used Bayes, yet ignored his plain-sight comments that EDA -- exploratory data analysis was what matters to most problem solvers; that CBA confirmatory data analysis was just an ornamental final flourish, and that was true for both bayesians and frequentists.[disclaimer: I wrote a book on EDA misleadingly titled 'Mastering statistics with your micro-computer' 1986]p 236 is to say the least, disingenuous! Greenspan, chairman of the Fed said in 2004 he used bayesian ideas to assess risk in financial policy. Ooops! He was proven spectacularly wrong by 2008! But Greenspan, claims Ms McGrayne didn't do Bayes properly. ho! ho! pull the other one!This is a good book, well researched, and shines a light on otherwise neglected characters (statisticians, like me!). But she's caught the bayesian bug in spades!

  • By David on 11 December 2012

    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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