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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 Two Centuries of Controversy Hardcover – May 17, 2011

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Editorial Reviews

Review

"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)

"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)

“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 2010-08-19)

“Compelling, fast-paced reading full of lively characters and anecdotes. . . .A great story.” —Robert E. Kass, Carnegie Mellon University

(Robert E. Kass)

"Makes the theory come alive. . .enjoyable. . .densely packed and engaging, . . .very accessible. . .an admirable job of giving a voice to the scores of famous and non-famous people and data who contributed, for good or for worse."—Significance Magazine
(Significance Magazine)

"A very compelling documented account. . .very interesting reading."—Jose Bernardo, Valencia List Blog
(Jose Bernardo Valencia List Blog)

"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."—New Scientist
(New Scientist)

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 2011-07-28)

"A lively, engaging historical account...McGrayne describes actuarial, business, and military uses of the Bayesian approach, including its application to settle the disputed authorship of 12 of the Federalist Papers, and its use to connect cigarette smoking and lung cancer...All of this is accomplished through compelling, fast-moving prose...The reader cannot help but enjoy learning about some of the more gossipy episodes and outsized personalities."—Choice
(Choice)

“McGrayne is such a good writer that she makes this obscure battle gripping for the general reader.”—Engineering and Technology Magazine
(Engineering and Technology Magazine)

"McGrayne explains [it] beautifully...Top holiday reading."—The Australian
(The Australian)

"Engaging....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....I was brought up, statistically speaking, as what is called a frequentist...But reading McGrayne's book has made me determined to try, once again, to master the intricacies of Bayesian statisics. I am confident that other readers will feel the same."—The Lancet
(The Lancet)

"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)

"A fascinating and engaging tale."—Mathematical Association of America Reviews
(Mathematical Association of America Reviews)

"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. Dale, Notices of the American Mathematical Society
(Andrew I. Dale Notices of the American Mathematical Society)

"A very engaging book that statisticians, probabilists, and history buffs in the mathematical sciences should enjoy."—David Agard, CryptologIA
(David Agard CryptologIA)

"Delightful ... [and] McGrayne gives a superb synopsis of the fundamental development of probability and statistics by Laplace."—Scott L. Zeger of Johns Hopkins, Physics Today 
(Physics Today Scott L. Zeger)

“Superb.”—Andrew Hacker, New York Review of Books 
(Andrew Hacker New York Review of Books)

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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Product Details

  • Hardcover: 336 pages
  • Publisher: Yale University Press (May 17, 2011)
  • Language: English
  • ISBN-10: 0300169698
  • ISBN-13: 978-0300169690
  • Product Dimensions: 6.1 x 1.1 x 9.2 inches
  • Shipping Weight: 1.4 pounds
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (107 customer reviews)
  • Amazon Best Sellers Rank: #145,546 in Books (See Top 100 in Books)

More About the Author

Sharon Bertsch McGrayne is the author of critically-acclaimed books about scientific discoveries and the scientists who make them. She is interested in exploring the cutting-edge connection between social issues and scientific progress--and in making the science clear, interesting and accurate for non-specialists.

Her latest book, The Theory That Would Not Die, tells how an 18th century approach to assessing evidence was vilified for much of the 20th century before--in an overnight sea change--it permeated our modern lives.

In a full-page review in the New York Times Book Review, John Allen Paulos wrote, "If you're not thinking like a Bayesian, perhaps you should be."

Editor's Choice, New York Times Book Review.

"I recently finished reading The Theory That Would Not Die. ... Bayes's rule is a statistical theory that has a long and interesting history. It is important in decision making -- how tightly should you hold on to your view and how much should you update your view based on the new information that's coming in. We intuitively use Bayes's rule every day ... "-- Alan B. Krueger, chair of President Obama's Council of Economic Advisers. Jan. 1, 2012, New York Times.

Nature called it, "A rollicking tale of the triumph of a powerful mathematical tool. ... An impressively researched history of Bayes' theorem."

"An example of the best in historical scientific journalism: it captures the main threads of the science while going much further on the human side of the story... This is a remarkable achievement. It taught me things, and it made me think. ... This book succeeds gloriously, by never losing sight of the story, and it's a wonderful story, one that desperately deserved to be told." --Robert E. Kass, Carnegie Mellon University

"McGrayne ... articulates difficult ideas in a way that the general public can understand and appreciate. ... I highly recommend it to anyone interested in science, history, and the evolution of a theorem over time. The book read as if it were a love story -- for an algorithm that grew up neglected, periodically taken out for a ride but mostly sitting home alone, until at long last, it finally found its rightful place of respect and appreciation in the world." --IEEE Computing Now.

The Boston Globe calls it "an intellectual romp, ... a masterfully researched tale of human struggle and accomplishment, and it renders perplexing mathematical debates digestible and vivid for even the most lay of audiences."

"Engaging. ... 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. ... I was brought up, statistically speaking, as what is called a frequentist... But reading McGrayne's book has made me determined to try, once again, to master the intricacies of Bayesian statisics. I am confident that other readers will feel the same." -- The Lancet.

"As significant in our times as the Darwinian theory of natural selection..., yet Bayes' Rule is almost unknown to a wide segment of the educated general public." -- Times Literary Supplement.

"McGrayne is such a good writer that the makes this obscure battle gripping for the general reader. [She writes] with great clarity and wit." Engineering and Technology Magazine.

James Berger, Arts & Sciences Professor of Statistics, Duke University, and a member of the National Academy of Sciences wrote, "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!"

"A Statistical Thriller... McGrayne's tale has everything you would expect of a modern-day thriller. Espionage, nuclear warfare and cold war paranoia all feature... a host of colourful characters and their bitter rivalries carry the tale... McGrayne's writing is luminous. ... 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."
-- NewScientist

"A compelling and entertaining fusion of history, theory and biography... McGrayne is adept at explaining abstruse mathematics in layperson's language."
-- Sunday London Times

"Approachable and engrossing. ... One of the 100 best holiday reads."
-- Sunday London Times

"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

"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, author of Understanding Uncertainty

"Many gripping and occasionally startling stories that grace Sharon Bertsch McGrayne's highly enjoyable new history of Bayesian inference. ... Actuaries play a particular notable role in McGrayne's hidden history of 20th century Bayes."
--Contingencies

"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

"Very compelling, ... very interesting reading."
-Jose Bernardo, Valencia List

"Makes the theory come alive, ... gives a voice to the scores of famous and non-famous people and data who contributed, for good or for worse."
-Significance Magazine

"Lively, engaging historical account... Compelling, fast-moving prose. ... Recommended."
-Choice

"McGrayne's book is not a textbook and does not attempt to teach Bayesian inferential techniques. Rather, McGrayne offers a very thorough, informative, and often entertaining (in our humble opinion) discussion of the Bayesian perspective... Strongly recommended [for students] as it provides the theoretical underpinnings of the Bayesian perspective and shows how Bayesianism has been applied to real world inferential / statistical problems."
-- Jon Starkweather, RSS Matters.

"An intellectual romp ... a masterfully researched tale of human struggle and accomplishment, and it renders perplexing mathematical debates digestible and vivid for even the most lay of audiences. Acknowledging ignorance is the first step toward knowledge, yes, and when we wed our ignorance with our better instincts we often find the best possible second step."
-- The Boston Globe.

Wiskunde die je laat leren van je onwetendheid.
-- NRC Handelsblad.

"McGrayne explains [it] beautifully. ... Top holiday reading."
-- The Australian.

OTHER BOOKS BY McGRAYNE

McGrayne's first book dealt with changing patterns of discrimination faced by leading women scientists during the 20th century. Another book portrayed a group of chemists and the interplay between science, the chemical industry, the public's love of creature comforts, and the environment.

McGrayne's work has been featured on the Charley Rose Show and reviewed in Nature, Physics Today, Significance, the Washington Post, Ms., JAMA, Chemistry and Engineering News (C&EN), New Scientist, American Scientist, PopularMechanics.com, and the like. She has appeared on NPR's Talk of the Nation: Science Friday and been invited to speak at more than twenty universities here and in Europe, at national laboratories such as Argonne National Laboratory and the National Institute of Science and Technology (NIST), and at the Centennial meeting of the American Physical Society.

She has written for Science, Scientific American, Discover Magazine, Isis, American Physical Society News, The Times Higher Education Supplement, and Notable American Women. Excerpts of her books have appeared in The Chemical Educator, The Physics Teacher, and Chemical Heritage Foundation Magazine. Nobel Prize Women in Science is used extensively in college courses in the United States and Europe. The National Academy of Sciences presented the Empress of Japan with a copy of the book and now publishes it.

McGrayne is a former prize-winning journalist for Scripps-Howard, Crain's, Gannett, and other newspapers and a former editor and co-author of extensive articles about physics for the Encyclopaedia Britannica. A graduate of Swarthmore College, she lives in Seattle, Washington.



Customer Reviews

Most Helpful Customer Reviews

241 of 248 people found the following review helpful By Sitting in Seattle on May 29, 2011
Format: Kindle Edition Verified Purchase
"The Theory That Would Not Die" is an enjoyable account of the history of Bayesian statistics from Thomas Bayes's first idea to the ultimate (near-)triumph of Bayesian methods in modern statistics. As a statistically-oriented researcher and avowed Bayesian myself, I found that the book fills in details about the personalities, battles, and tempestuous history of the concepts.

If you are generally familiar with the concept of Bayes' rule and the fundamental technical debate with frequentist theory, then I can wholeheartedly recommend the book because it will deepen your understanding of the history. The main limitation occurs if you are *not* familiar with the statistical side of the debate but are a general popular science reader: the book refers obliquely to the fundamental problems but does not delve into enough technical depth to communicate the central elements of the debate.

I think McGrayne should have used a chapter very early in the book to illustrate the technical difference between the two theories -- not in terms of mathematics or detailed equations, but in terms of a practical question that would show how the Bayesian approach can answer questions that traditional statistics cannot. In many cases in McGrayne's book, we find assertions that the Bayesian methods yielded better answers in one situation or another, but the underlying intuition about *why* or *how* is missing. The Bayesian literature is full of such examples that could be easily explained.

A good example occurs on p. 1 of ET Jaynes's Probability Theory: I observe someone climbing out a window in the middle of the night carrying a bag over the shoulder and running away. Question: is it likely that this person is a burgler?
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42 of 45 people found the following review helpful By Denys Yeo on June 5, 2011
Format: Hardcover Verified Purchase
This book moves through the history (so far) of the development and application of Bayes rule. It is a good story, and the book is well written. Unfortunately, it is somewhat mixed in the manner material is presented. For example, the author provides significant detail on the application of the rule to activities such as code cracking and finding submarines but she then goes on to list a large number of more recent applications with very little historical background. Maintaining consistency of depth for each application discussed would have significantly improved the "story". I would recommend this book to anyone who is interested in the history of science, statistics and mathematics, but be prepared for a "patchy" read.
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336 of 412 people found the following review helpful By Herbert Gintis on June 17, 2011
Format: Hardcover Verified Purchase
Sharon Bertsch Mcgrayne is a talented science writer whose portraits of great scientists of the past are incisive and entertaining. However, she evidently believes that one must studiously avoid dealing with any serious scientific issues in entertaining a popular audience. For this reason, this book is a total failure. Why should a reader care about the history of an idea of which he or she has zero understanding? Mcgrayne turns the history of Bayes rule into a pitched battle between intransigent opponents, but we never find out what the real issue are.

In fact, Bayes rule is a mathematical tautology, being the definition of conditional probability. Suppose A is an event with probability P(A) and B is an event with probability P(B). Let C be the event "both A and B occur." Then the conditional probability P(A|B) of event A, given that we know that B has occurred, just P(C)/P(B). Moreover, if a decision-maker knows P(A), P(B), and P(C), and discovers that B occurred, then he should revise the probability that A occurred to P(A|B) = P(C)/P(B). Why? Well, suppose we have a population of 1000 individuals, where the probability that an event E is true of an individual is P(E), where E is any one of A, B, and C. Then the expected number of individuals for which B is true is 1000*P(B). Of these, the number for which A is also true is 1000*P(A). Therefore, the probability that an individual satisfies A, given that he satisfies B, is 1000*P(A)/1000*P(B) = P(A|B).

For instance, suppose 5% of the population uses drugs, and there is a drug test that is correct 95% of the time: it tests positive on a drug user 95% of the time, and it tests negative on a drug nonuser 95% of the time.
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18 of 20 people found the following review helpful By Charles A. Ellis MD on August 26, 2011
Format: Hardcover Verified Purchase
While I completely agree with those reviewers who expressed disappointment with the lack of technical depth in the author's presentation, what I find even more disturbing is her abuse of reference material. References appear in two sections: in footnotes to each chapter, and then, again, as a bibliography with separate sections for each of the book chapters. This leads to some (expected and excusable) duplication, but there are indefensible gaps, in which footnotes may refer to books or articles that cannot be found in any of the bibliographies, let alone in those dedicated to the footnoted chapter. It is even more unfortunate that many of the references given do not permit the interested reader to fill in the technical and scientific detail of the applications the author so temptingly describes, or, in the case of the missing H-bomb, seems to describe. One is driven to the conclusion that almost none of the text pertains to actual application of Bayes' Rule, or, indeed, to any sort of statistical analysis.

It is quite true that the historical presentation is replete with biographical anecdotes, and they are a joy to those of us interested in the history of statistics (and philosophy and logic) - but, alas, that makes even more frustrating the utter absence of technical, mathematical detail.

Though much of the book purports to be a presentation of the Bayesian vs. Frequentist controversy, it deals with the latter no more deeply or fruitfully than the former. In brief, it is truly a "hands-off" presentation, hence immensely disappointing. If only it were the book the jacket blurbs describe!
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