The Theory That Would Not Die, by science writer Sharon Bertsch McGrayne, aims to track the history and emerging applications of Bayes’ theorem, a statement from probability theory that holds a ubiquitous presence in much of contemporary statistics and data science. The theorem specifies a technical means by which the estimated probability of a future event occurring can be updated in the face of new evidence.
The book, addressed to nontechnical readers, is subtitled, How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. Indeed, the applications of the theorem are enormously wide-ranging, with use cases from DNA decoding to homeland security. In spite of its versatility, its use was limited for most of its 250-year history, due to its somewhat counterintuitive nature and an unwillingness on the part of some prominent members of the statistical community to adopt it in their research.