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The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century Paperback – May 1 2002

4.1 out of 5 stars 26 customer reviews

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Product Details

  • Paperback: 352 pages
  • Publisher: Holt Paperbacks; 1 edition (May 1 2002)
  • Language: English
  • ISBN-10: 0805071342
  • ISBN-13: 978-0805071344
  • Product Dimensions: 14 x 2.3 x 20.8 cm
  • Shipping Weight: 340 g
  • Average Customer Review: 4.1 out of 5 stars 26 customer reviews
  • Amazon Bestsellers Rank: #141,780 in Books (See Top 100 in Books)
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Product Description

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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 --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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Top Customer Reviews

Format: Paperback
This is another of those books about mathematics that avoids displaying any mathematical equations or formulas, like Stephen Hawking's "A Brief History of Time." Hawking explained that his publishers told him that every line of mathematics would cut the sales by 50%. Unfortunately, the lack of mathematics makes it much harder to transmit the ideas. In many places in this book, I miss the math sorely. This book is actually harder to understand as it is, then if it gave us the relevant equations and formulas. Maybe Salsburg (or some other generous soul) could put together a web site that provides the math, referenced to chapters in the book.
Nevertheless, the book tells its stories well, and rewards (and challenges) the reader with some ideas and concepts I'd like to at least remember, if not explore further.
Chapter seven briefly outlines "the Fisherian versus the Pearsonian view of statistics," a philosophical theme that is fundamental to the application of statistics to reality. "Karl Pearson viewed statistical distributions as describing the actual collections of data he would analyze. According to Fisher, the true distribution is an abstract mathematical formula, and the data collected can be used only to estimate the parameters of the true distribution.... Pearson viewed the distribution of measurements as a real thing.... To Fisher, the measurements were a random selection from the set of all possible measurements." I'm not sure what this means, exactly.
At the end of chapter six, there is a review of a math text (Gumbel's "Statistics of Extremes," an out of print collectible being offered through amazon...) from the 1950's that makes me want to find the book and read it.
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Format: Hardcover
I am a high school math teacher who has long thought that statistics is more important in the curriculum than calculus. This book is one I can now recommend to colleagues and parents who question the importance of the subject. (Usually these adults had miserable experience with statistics courses in the past where formulas and computation, rather than understanding, drove the class.)
This book accomplishes two things. First, it conveys the development of statistics in the 20th century as the science of science - i.e. how experiments and surveys form the basis for knowledge and how to evaluate that knowledge. Second, it puts a human face on those who contributed to the field. The author's stories of Fisher vs. Neyman are wonderful. I especially appreciated how Salsburg relates the role of women in the field. They were often would-be mathematicians who were directed into statistics as a more "appropriate" field for women. Fortunately, as government use of statistics expanded, women civil servants were often already in place to provide quality analysis.
This book will probably not be widely read, but it should be...especially by scientists, journalists, and teachers.
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Format: Hardcover
This book is loaded with technical terms that are barely explained. True, the stories of the people involved in developing these ideas are presented in a vivid and clear style. But this does little to aid the reader in grasping these mathematical concepts so that they have meaning. After all, this book asserts that statistics has revolutionized science, and I did not feel anything like this at the end of this book. Moreover, the author glibly rejects all of chaos theory in a little bit more than 3 pages[93-6], at another point calls the law of cause and effect " a vague notion that will not withstand the batterings of pure reason"[ p 186] But what "pure reason" happens to be, the author never bothers to tell us. Moreover, he earlier asserts that "the statistical model that defines the quest of also based on a statement of faith." This comment then merits a discussion of what axioms are being put forth. But again there is a conspicuous vacuum of thought.At the conclusion, Salsburg casts doubt on the entire subject of his book by stating :"I do not believe that the human mind is capable of organizing a structure of ideas that can come close to describing what is really out there." This self-contradiction coming from the mouth of a supposed science educator is a perfect reflection of the philosophical mess that constitutes this book. Not recommended.
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Format: Hardcover
Most people don't realize that the very notion of proof, at least in the field of medicine, did not exist until 1934, when the founder of modern statistics, R.A. Fisher, invented it. He would undoubtedly have some scathing remarks on what currently passes for proof for new medical treatments. You'll read about all the great statisticians of the 20th century, many of whom fled the Nazi's, or the Russians, and wound up in the United States. One accomplished American statistician was laid off by Department of Agriculture bureaucrats in the great Depression and could only find a job in the Soviet Union under Stalin. What a great story! I met some of these guys at Stanford when I was getting my Masters Degree in Statistics in the 1970s. While they sometimes can be boring on the surface, underneath lurks a passion for reality rarely found in more superficially interesting folk. I used the text of Gumbel on how to compute the probability of a 100 year flood as the basis of my Ph.D. thesis on carcinogenesis at the University of Colorado School of Medicine Department of Biometrics in the 1980s. As a well rounded technologist, Gumbel also published a book on Four Years of Political Murder in 1922, followed by Causes of Political Murder in 1928, as a critique of the Nazis. When the Nazis came to power in 1933, he barely escaped Germany and had to hide out in Southern France. This is the best book of this type that I've read since Fermat's Enigma and it is best savored chapter by chapter over a cup of cappuccino in a Peets or Starbucks. A book for the general reader that every statistician should read!
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