Description

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Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.

In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-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.

About the Author

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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.

Praise For…

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"If you''re not thinking like a Bayesian, perhaps you should be."—John Allen Paulos, The New York Times Book Review
-John Allen Paulos

“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

“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

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

"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

"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

“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

"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

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

"McGrayne explains [it] beautifully...Top holiday reading."—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