Science is inextricably linked with mathematics. Statistician David Salsburg examines the development of ever-more-powerful statistical methods for determining scientific truth in The Lady Tasting Tea
, a series of historical and biographical sketches that illuminates without alienating the mathematically timid. Salsburg, who has worked in academia and industry and has met many of the major players he writes about, shares his subjects' enthusiasm for problem solving and deep thinking. This drives his prose, but never at the expense of the reader; if anything, the author has taken pains to eliminate esoterica and ephemera from his stories. This might frustrate a few number-head readers, but the abundant notes and references should keep them happy in the library for weeks after reading the book.
Ultimately, the various tales herein are unified in a single theme: the conversion of science from observational natural history into rigorously defined statistical models of data collection and analysis. This process, usually only implicit in studies of scientific methods and history, is especially important now that we seem to be reaching the point of diminishing returns and are looking for new paradigms of scientific investigation. The Lady Tasting Tea will appeal to a broad audience of scientifically literate readers, reminding them of the humanity underlying the work. --Rob Lightner
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From Publishers Weekly
The development of statistical modeling in primary research is the underreported paradigm shift in the foundation of science. The lady of the title's claim that she could detect a difference between milk-into-tea vs. tea-into-milk infusions sets up the social history of a theory that has changed the culture of science as thoroughly as relativity did (the lady's palate is analogous to quantum physics' famous cat-subject), making possible the construction of meaningful scientific experiments. Statistical modeling is the child of applied mathematics and the 19th-century scientific revolution. So Salsburg begins his history at the beginning (with field agronomists in the U.K. in the 1920s trying to test the usefulness of early artificial fertilizer) and creates an important, near-complete chapter in the social history of science. His modest style sometimes labors to keep the lid on the Wonderland of statistical reality, especially under the "This Book Contains No Equations!" marketing rule for trade science books. He does his best to make a lively story of mostly British scientists' lives and work under this stricture, right through chaos theory. The products of their advancements include more reliable pharmaceuticals, better beer, econometrics, quality control manufacturing, diagnostic tests and social policy. It is unfortunate that this introduction to new statistical descriptions of reality tries so hard to appease mathophobia. Someone should do hypothesis testing of the relationship between equations in texts and sales in popular science markets it would make a fine example of the use of statistics. Illus.
Copyright 2001 Cahners Business Information, Inc.
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