The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition, and Society)

The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition, and Society)
by Deirdre Nansen McCloskey, Steve Ziliak

The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition, and Society)
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Book Summary Information

Author: Deirdre Nansen McCloskey, Steve Ziliak
Edition: Paperback
Published: 2008-02-19
ISBN: 0472050079
Number of pages: 352
Publisher: University of Michigan Press

Book Reviews of The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition, and Society)

Book Review: Mean-spirited and Misguided
Summary: 2 Stars

I attended a seminar by McCloskey when she announced she was working on this then-upcoming book. So I knew beforehand that its style would be more like a victim-tells-all revenge than a fun-seeking discovery typical of most popular science books. The first half of the book (up to Chapter 13) did turn out to be bitter. However, at least that part was largely based on facts, such as a comprehensive count of academic papers failing to meet certain standards. The second half of the book was devoted to the biographies of key persons who led to the rise of what the authors called the "cult of statistical significance". The book lost any pretense of integrity at that point, and just started slinging muds. Gosset was portrayed as a good-natured figure who worked hard like a bee; and Fisher, a mad scientist who stole the labor of others and would attack people by any means to defend his status. At one point the authors didn't even bother to call Fisher by his name, and just referred to him as the Wasp. They also dragged Fisher's mother into the ordeal by making suggestions that she was responsible for turning Fisher into a cold-hearted person that they claimed.

I was not only disgusted by this kind of tabloid sensationalism, but was also disappointed by how little useful information I got out of this long-awaited book. The authors "irrationalized" the popularization of statistical significance by framing it as the work of a cult. To further illegitimatize the use of statistical significance, they argued that it is wrong to rely on it to evaluate scientific hypotheses because (1) what we really want is how likely for a hypothesis to be true given the data, not the other way around; and (2) there are other clues just as, if not more, important, especially the effect size. These could have been reasonable positions if they did not make statistical significance a scapegoat for being a "fallacy" just because it is defined on the likelihoods of observing data given the hypotheses. As the way it is defined, statistical significance provides a measure of precision. That's all. Just because it doesn't answer all the questions of scientific interest doesn't mean it provides no useful information and certainly doesn't automatically make it a fallacy. Furthermore, many hypothesis tests used in academic researches are based on likelihood "ratios" rather than just the conditionals. At least there would be NO fallacy for the believers of the Likelihood Principle. It is quite regrettable that they fail to elaborate on such crucial information to make other people look stupid, whether it was their intention or not. As for the second point, I agree that researchers should have paid more attention to other factors, such as statistical power and sample size, IN ADDITION TO statistical significance. But I think it is misguided to hail any ban on reporting statistical significance as a heroic act of revolt as the authors did in the book. One can report all the effect sizes he wants. But it all means nothing if his inferences are what they appear to be mostly due to "bad luck" in sampling the wrong subjects.

If my views above are on the right track, then this book would serve the research community no good by martyrizing Gosset and demonizing Fisher. There has been no cult all along. If we are justified in believing that some vested interests overemphasized statistical significance to divert our attention away from the more important issues, then we should encourage people (authors and readers alike) to focus on those more important issues instead of treating statistical significance as if it were irrelevant. For a more serious and more informative discussion on this topics, I would recommend Chow's Statistical Significance: Rationale, Validity and Utility (Introducing Statistical Methods) . His first chapter explains the key issues in 12 pages with more varieties of arguments and more intellectually stimulating details than what Ziliak and McClosky attempted in 251 pages.

I give 3 stars for this book's good intent but average quality, and, on top of that, took 1 star off for its mean-spirited rhetorics.

Summary of The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition, and Society)

“McCloskey and Ziliak have been pushing this very elementary, very correct, very important argument through several articles over several years and for reasons I cannot fathom it is still resisted. If it takes a book to get it across, I hope this book will do it. It ought to.”

—Thomas Schelling, Distinguished University Professor, School of Public Policy, University of Maryland, and 2005 Nobel Prize Laureate in Economics

“With humor, insight, piercing logic and a nod to history, Ziliak and McCloskey show how economists—and other scientists—suffer from a mass delusion about statistical analysis. The quest for statistical significance that pervades science today is a deeply flawed substitute for thoughtful analysis. . . . Yet few participants in the scientific bureaucracy have been willing to admit what Ziliak and McCloskey make clear: the emperor has no clothes.”

—Kenneth Rothman, Professor of Epidemiology, Boston University School of Health

The Cult of Statistical Significance shows, field by field, how “statistical significance,” a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ “testing” that doesn’t test and “estimating” that doesn’t estimate. The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots.

Stephen T. Ziliak is the author or editor of many articles and two books. He currently lives in Chicago, where he is Professor of Economics at Roosevelt University. Deirdre N. McCloskey, Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago, is the author of twenty books and three hundred scholarly articles. She has held Guggenheim and National Humanities Fellowships. She is best known for How to Be Human* Though an Economist (University of Michigan Press, 2000) and her most recent book, The Bourgeois Virtues: Ethics for an Age of Commerce (2006).

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