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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"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 "
"If you're not thinking like a Bayesian, perhaps you should be."--John Allen Paulos, "New York Times Book Review"--John Allen Paulos "New York Times Book Review "
"[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 "
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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Top Customer Reviews
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.Read more ›
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.
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.
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.Read more ›
Most Recent Customer Reviews
Very well written book - well structured, entertaining and researched. A useful introduction to Bayes theorem and application. Read morePublished 28 days ago by Ralph Hickman
I wish there had been greater clarity on how Baye's theorem works by way of more practical examples. Also, I would like to have seen the mathematical proof of the theorem. Read morePublished 11 months ago by Ron Brower
This is an okay book, it's not very mathematical, more of a historical overview.Published 11 months ago by barbie
The problem with this book is that it never explains exactly HOW Bayes Rule is used to estimate risks or probabilities. Read morePublished 11 months ago by Dr. Julian G. Edwards
Very interesting read for the mathematically minded or challenged.Published 12 months ago by Jamal Mills
A well written historical insight to the journey of a theory that is now used all over but is still seldom heard of
Lovely insights into the politics of science and how... Read more
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