The theory that would not die: how Bayes' rule cracked the enigma code, hunted down Russian submarines, & emerged triumphant from two centuries of controversy
Description
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.
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9781452626857
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Published Reviews
Choice Review
When Reverend Thomas Bayes's posthumous essay on the calculation of inverse probability appeared in 1763, few might have expected the intellectual controversies that it would generate for centuries to come. Indeed, Bayes's deceptively simple rule for updating prior belief with subsequent observation fundamentally affected the practice of modern statistics, and science writer McGrayne (Prometheus in the Lab, CH, Feb'02, 39-3391) provides a lively, engaging historical account of many of its consequences. She 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. In particular, she notes the intense division that developed between Bayesians and frequentists as statistics developed as a coherent quantitative discipline in the 20th century. All of this is accomplished through compelling, fast-moving prose, and the reader cannot help but enjoy learning about some of the more gossipy episodes and outsized personalities. However, in her attempt to appeal to a general audience, McGrayne offers little technical discussion. As a result, readers unfamiliar with statistics likely will not be able to appreciate the equally engrossing scientific story in meaningful detail. Summing Up: Recommended. Informed general readers and academic students. S. J. Colley Oberlin College