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Library | Call Number | Material Type | Home Location | Status | Item Holds |
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Searching... | Q175 .S2345 2001 | Adult Non-Fiction | Non-Fiction Area | Searching... | Searching... |

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### Summary

### Summary

At a summer tea party in Cambridge, England, a lady states that tea poured into milk tastes differently than that of milk poured into tea. Her notion is shouted down by the scientific minds of the group. But one guest, by the name Ronald Aylmer Fisher, proposes to scientifically test the lady's hypothesis. There was no better person to conduct such a test. For Fisher had brought to the field of statistics an emphasis on controlling the methods for obtaining data and the importance of interpretation. He knew that how the data was gathered and applied was as important as the data themselves.In The Lady Tasting Tea , readers will encounter not only Ronald Fisher's theories (and their repercussions), but the ideas of dozens of men and women whose revolutionary work affects our everyday lives. Writing with verve and wit, author David Salsburg traces the rise and fall of Karl Pearson's theories, explores W. Edwards Deming's statistical methods of quality control (which rebuilt postwar Japan's economy), and relates the story of Stella Cunliff's early work on the capacity of small beer casks at the Guinness brewing factory. The Lady Tasting Tea is not a book of dry facts and figures, but the history of great individuals who dared to look at the world in a new way.

### Author Notes

David Salsburg is a former senior research fellow at Pfizer, Inc., and currently works as a private consultant. Also a former university professor, he lives in New London, Connecticut.

### Reviews 2

### Publisher's Weekly Review

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. (Apr.) (c) Copyright PWxyz, LLC. All rights reserved

### Library Journal Review

This is an insightful and revealing history of how the emergence of statistics in scientific research revolutionized the sciences. Without using a single mathematical equation, Salsburg, a former Harvard professor and a prolific writer with three books and numerous articles on applied statistics, clearly discusses some major advances in statistics in the last century. He covers most of the major contributors to the field and dedicates two chapters to the contributions made by women. Salsburg also does an excellent job of showing how statistics has had an impact in the development of other sciences likes agriculture, cancer research, and econometrics as well as its influence in industry, where statistical methods are widely used in quality control and for the analysis of operational research. General readers with little mathematical background will be able to grasp Salsburg's lucid concepts with ease. Specialists will also enjoy reading this book for its interesting presentation and for the many biographical notations about some of the most influential researchers in the field. Since Salsburg focuses on the 20th century, readers interested in learning about earlier developments in statistics can look at Stephen M. Stigler's Statistics on the Table (LJ 10/1/99). Nestor L. Osorio, Northern Illinois Univ. Lib., DeKalb (c) Copyright 2010. Library Journals LLC, a wholly owned subsidiary of Media Source, Inc. No redistribution permitted.