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The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century 1St Edition Edition

4.2 out of 5 stars 116 customer reviews
ISBN-13: 978-0805071344
ISBN-10: 0805071342
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Editorial Reviews

Amazon.com Review

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 illuminate 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. His sense of excitement drives the 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 --This text refers to an out of print or unavailable edition of this title.

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.

--This text refers to an out of print or unavailable edition of this title.
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Product Details

  • Paperback: 352 pages
  • Publisher: Holt Paperbacks; 1St Edition edition (May 1, 2002)
  • Language: English
  • ISBN-10: 0805071342
  • ISBN-13: 978-0805071344
  • Product Dimensions: 5.5 x 0.9 x 8.2 inches
  • Shipping Weight: 12 ounces (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (116 customer reviews)
  • Amazon Best Sellers Rank: #40,884 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By Michael R. Chernick on January 24, 2008
Format: Hardcover
The Lady Tasting Tea is a new book by David Salsburg (a Ph.D. mathematical statistician, who recently retired from Pfizer Pharmaceuticals in Connecticut). The title of the book is taken from the famous example that R. A. Fisher used in his book "The Design of Experiments" to express the ideas and principles of statistical design to answer research questions. The subtitle "How Statistics Revolutionized Science in the Twentieth Century" really tells what the book is about. The author relates the statistical developments of the 20th Century through descriptions of the famous statisticians and the problems they studied.

The author conveys this from the perspective of a statistician with good theoretical training and much experience in academia and industry. He is a fellow of the American Statistical Association and a retired Senior Research Fellow from Pfizer has published three technical books and over 50 journal articles and has taught statistics at various universities including the Harvard School of Public Health, the University of Connecticut and the University of Pennsylvania.

This book is written in layman's terms and is intended for scientists and medical researchers as well as for statistician who are interested in the history of statistics. It just was published in early 2001. On the back-cover there are glowing words of praise from the epidemiologist Alvan Feinstein and from statisticians Barbara Bailar and Brad Efron. After reading their comments I decided to buy it and I found it difficult to put down.

Salsburg has met and interacted with many of the statisticians in the book and provides an interesting perspective and discussion of most of the important topics including those that head the agenda of the computer age and the 21st century.
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Format: Hardcover
David Salsburg's book "The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century" (W.H. Freeman & Co., 340 pp., $23.95) celebrates the lives of two dozen great statisticians.
Short biographies of statistical innovators -- such as Francis Galton, Karl Pearson, Edward Deming, John Tukey and the most important of all, Ronald A. Fisher -- might seem of limited interest. Yet, over the past century, statisticians probably have done more to help us understand the real world than philosophers, who are endlessly profiled in countless books.
When discussing what has helped him in his work, Nobel Laureate physicist Stephen Weinberg has undiplomatically referred to "the unexpected uselessness of philosophy," while praising the "unexpected usefulness of mathematics."
The fecklessness of philosophy stems in part from the anti-statistical bias of the central tradition in European philosophy. Going back to Plato, philosophers have tended to assume that reality is based on abstract essences that could be described by geometry or words. In truth, though, the natural and human worlds appear to be probabilistic affairs. Statistics have thus proven crucial for describing subjects as commonplace as differences in human intelligence, as esoteric as quantum mechanics, and as life-or-death as the testing of new medicines.
This ignorance of statistics also plagues our public life. Veteran pundit James J. Kilpatrick has rightly argued that young journalists absolutely ought to study statistics in college.
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Format: Hardcover
The title refers to the story about the English lady who believed she could tell by tasting whether the milk had been added to the tea or the tea added to the milk. We find out here that apparently she could. At least in the small sample of cases recorded, she "identified every single one of the cups correctly." (p. 8)
The question--and this is the question that statisticians are forever trying to answer--is, was the result significant? Or how much faith should we put in such a result? What is the probability that such a result comes to us by chance rather than by causation? Did she simply guess right ten times in a row? Or, more saliently, how many times would she have to guess right before you'd be a believer? Or, more rigorously, how many times out of how many trials would she have to guess right before we can be confident that she isn't just guessing?
Statistics then is a way of understanding and appreciating events without reference to causation. How cigarette smoking causes lung cancer is not exactly known. The fact that cigarette smoking does indeed cause lung cancer is demonstrated by a clear statistical correlation between smoking and the instance of lung cancer. But is a statistical correlation proof?
Salsburg's very readable book is a narrative about the mathematicians who have tried to answer this and other statistical questions. The emphasis is on the mathematicians themselves, not on their mathematics. Indeed, following a time-honored "rule" in the book publishing business, a rule that insists that you lose "x" number of readers for every mathematical formula that appears on your pages, Salsburg has elected to use a grand total of zero.
I was a little disconcerted about this.
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