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

111 customer reviews
ISBN-13: 978-0805071344
ISBN-10: 0805071342
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Editorial Reviews 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 (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 (111 customer reviews)
  • Amazon Best Sellers Rank: #32,215 in Books (See Top 100 in Books)

More About the Author

David Salsburg has his PhD in mathematical statistics and has taught at the University of Pennsylvania, Harvard School of Public Health, Yale University, Connecticut College, and the University of Connecticut. Most of his career was spent at Pfizer Central Research, Pfizer, Inc., where he rose to the top of the scientific ladder. He was the first statistician hired at Pfizer and among the first to work for any drug company.

In 1962, amendments to the Food and Drug Law of the U.S. gave the Food and Drug Administration authority to require that the sponsors of new drugs prove that the drugs were effective for the medical indications. Before this, they had only to prove that the new drug was "safe". Management at Pfizer thought they were hiring someone to calculate something called a p-value to provide a statistical gloss to what they already "knew". However, the main advantage of statistical modeling is that it forces the scientist to think carefully about the possible outcomes of the study and about the careful design of the study. Salsburg soon found himself doing more than calculating p-values. He began poking into problems in pharmacology, toxicology, chemistry, and even marketing. Management came to realize that they could use statisticians for more than calculating a p-value but for making the earlier decisions about development. In the end, Salsburg contributed to the development of several hundred compounds that failed to make it to market, and 20 that did.

He retired from Pfizer in 1995 and has since taught at Harvard and Yale and written several books. His LADY TASTING TEA described the development of statistical models in language designed for the non-expert reader. His JONAH IN THE GARDEN OF EDEN (now available as an e-book on Kendle) uses statistical methods to examine the authorship of the books of the Hebrew Bible. He has published articles examining the authorship of books attributed to Davy Crockett, and looking at the authenticity of collections of numbers found in the Bible.

As he enters his 90th decade, he is busy lecturing, writing, visiting grandchildren. See his blog for some of his ideas and comments

Customer Reviews

Most Helpful Customer Reviews

53 of 54 people found the following review helpful By Charles Ashbacher HALL OF FAMETOP 500 REVIEWERVINE VOICE on January 1, 2002
Format: Hardcover
I have taken courses in statistics, taught it many times and solved several statistical problems that have appeared in journals. But until I read this book, I never really thought about it in so deep and philosophical a manner. Which is most unusual, in that it is a book written to a popular audience. Some of the very deep and critical problems raised consider questions such as, "How do you deal with outliers?" An outlier is a data point that differs from the others by a great deal. The fact that it is a data point means that it is part of the sample, but the large differences from the others means that there are valid reasons to consider it flawed. Given these differences, including or excluding an outlier can lead to substantial changes in the results.
Other issues concern the accuracy of measurement, for example, when can specific tests be applied and what consequences can be associated with the results. We saw an example of such complexity in the 2000 presidential election in the United States. The vote was essentially a tie, with the differences being well within all possible measures of sampling error. As some of the wiser news commentators pointed out, it is impossible to count every vote, an election is only an approximation of the true, unknown value. No statistician could have said it better.
Given the context, Plato's idea of the abstract form appears in this history of the development of statistics as a discipline separate from mathematics. A statistical sample is only an estimate of a value that will never be known. The key is to get an approximation that is close enough to be usable in whatever the current context is. In this respect, statistics is like engineering, where the interest is in getting usable, rather than precise information.
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57 of 59 people found the following review helpful 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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112 of 123 people found the following review helpful By Amazon Customer on July 16, 2001
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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