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The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, & Emerged Triumphant from Two Centuries of C-Sharon Bertsch McGrayne

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"This account of how a once reviled theory, Baye’s rule, came to underpin modern life is both approachable and engrossing" (Sunday Times).  A New York Times Book Review Editors’ Choice 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 generations-long human drama surrounding it.   McGrayne traces the rule’s discovery by an 18th century amateur mathematician through its development by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—while practitioners relied on it to solve crises involving great uncertainty and scanty information, such as Alan Turing's work breaking Germany's Enigma code during World War II.   McGrayne also explains how the advent of 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.

Book The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, & Emerged Triumphant from Two Centuries of C Review :



This book blew my mind. Most of the examples used and the mathematicians involved I was familiar with, but not the Bayesian angle. I feel like the wool was pulled away from my eyes after reading this book. Other reviews complain about the lack of math in the main text of the book, but I disagree. One I think anyone reading this book knows Bayes Rule and two I think the actual math would get in the way of the story. One of the biggest themes of the book is that Bayes is about practical problem solving and that once computers arrived on scene to allow for the iterative brute force solving that it really took off. The process or way of thinking is made clear in the text. Really it was great read, I found myself texting people while reading saying did you know this was Bayes, over and over.
The historical anecdotes in the book might be interesting to people who use/read statistical analyses in their work as I do. However, don't read this book if you expect to learn how to actually apply Baye's rule or conditional probability. I might have given this book 3 stars but there is a terrible error in the appendix explaining how to apply Baye's rule to breast cancer test results. THE ONLY CONCRETE EXAMPLE IN THE BOOK IS WRONG! What a disappointment. And for those of you who are confused by the results in the appendix: P(B|A) = 32/40 not 32/10000.

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