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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 MP3 CD – Audiobook, MP3 Audio, Unabridged
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About the Author
Laural Merlington has recorded well over one hundred audiobooks and has received several AudioFile Earphones Awards, including one for Never Say Die by Susan Jacoby.
More About the Author
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."
"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."
"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."
"Lively, engaging historical account... Compelling, fast-moving prose. ... Recommended."
"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.
Top Customer Reviews
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?Read more ›
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.Read more ›
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!
Most Recent Customer Reviews
Why title your book 'How' if you have no intention of explaining how? There is almost nothing at all about Bayes theorem in this book. Read morePublished 1 month ago by photondancer
Sounds like poor man's Asimov. An interesting subject, I would say even transcendent, reduced to "historical" facts, quick biographies of the involved scientists, unclear,... Read morePublished 1 month ago by Massimo Tagliavini
This book is very uneven and muddled. The author, Sharon McGrayne, has obviously done an incredible amount of research, so one star is avoided. Read morePublished 1 month ago by Daniel A Goldman
Very interesting book. It has inspired me to learn more about Bayes' Inference.Published 2 months ago by James B. Young
This is a very interesting/entertaining read. Although it is probably good to at least know the basic Bayesian equation, this is not required - the book is a non-technical,... Read morePublished 2 months ago by Jeff McNair
You need to know something about Bayesian Statistics, "Bayesian reasoning" and the Bayesian vs Classical Statistics problems in general to appreciate the book and you will... Read morePublished 3 months ago by Mauricio Gonzalez
Great book with excellent well researched content. The reason that the overall score isn't five stars is largely due to the anti-bayesians that still exist.Published 3 months ago by Captain
If you're interested in the history of Bayesian thinking and methods, this book is for you. Well written and easy to read.Published 5 months ago by Juan C Bujeda