"Statistical significance," a technique that dominates medicine, economics, psychology, and many other scientific fields, has been a huge mistake. The outcome is a case study in bad science - how it originates and how it grows. These sciences, from agronomy to zoology, the authors find, engage "testing" that doesn't test and "estimating" that doesn't estimate. Heedless of magnitude and of a genuine engagement with alternative hypotheses, they "testimate." "Null hypothesis significance testing" is in other words a scientific train-wreck, about which a small group of statisticians have been warning for a century.Ziliak and McCloskey's book shows field by field how the wreck happened, reports on the fatalities, and offers a quantitative way forward. The facts will startle the outside reader: how could a group of brilliant scientists wander so far away from scientific magnitudes? And it will inspirit the scientists who seek conscious interpretations of "oomph" rather than arbitrary columns of t-tests: how can the statistical sciences get back on track, and fulfill their quantitative promise?Ziliak and McCloskey measure the disaster in their home field of economics, and in psychology, epidemiology, and medical science. They touch as well on law, biology, psychiatry, pharmacology, sociology, political science, education, forensics, and other fields in the grip of "significance." This 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. Many statisticians have complained about it before, but have complained science-by-science.
A significant problem 1
1 Dieting "significance" and the case of Vioxx 23
2 The sizeless stare of statistical significance 33
3 What the sizeless scientists say in defense 42
4 Better practice: [beta]-importance vs. [alpha]-"significance" 57
5 A lot can go wrong in the use of significance tests in economics 62
6 A lot did go wrong in the American Economic Review during the 1980s 74
7 Is economic practice improving? 79
8 How big is big in economics? 89
9 What the sizeless stare costs, economically speaking 98
10 How economics stays that way: the textbooks and the referees 106
11 The not-boring rise of significance in psychology 123
12 Psychometrics lacks power 131
13 The psychology of psychological significance testing 140
14 Medicine seeks a magic pill 154
15 Rothman's revolt 165
16 On drugs, disability, and death 176
17 Edgeworth's significance 187
18 "Take 3[sigma] as definitely significant": Pearson's rule 193
19 Who sits on the egg of Calculus Canorus? not Karl Pearson 203
20 Gosset: the fable of the bee 207
21 Fisher: the fable of the wasp 214
22 How the wasp stung the bee and took over some sciences 227
23 Eighty years of trained incapacity: how such a thing could happen 238
