"[Steve Ziliak and Deirdre McCloskey] explain to us why the misunderstanding of statistical significance has lead to bad government policy making and how one particularly famous brewery employed the technique to improve the pints we enjoy today."
—Tim Harford, BBC
(Tim Harford BBC
"Despite appearing to be a book of limited appeal - it is after all a book that looks at a set of statistical techniques - it is one that has immense social implications. We live in an age where ideologies have largely been cast aside and instead we are governed increasingly by a class of politicians and civil servants who aim for 'evidence-based' policy-making. When that evidence is based on statistically significant results that ignore any quantification of results then we all have reason to pay attention."
—London Book Review
(NA London Book Review
"Persuading professionals that their procedures are wrong is a long and lonely task. McCloskey, joined later by Ziliak, has been conducting such a crusade against the misuse of significance testing for over 25 years. This book presents their argument, gives lots of examples of the adverse consequences of misuse, and provides some history of the controversy, which dates from the origins of mathematical statistics."
—Ron P. Smith, Journal of Economic Issues
(Ron P. Smith Journal of Economic Issues
"The Cult of Statistical Significance
has virtues that extend beyond its core message. It is clearly written and should be accessible to those who have neither formal training in statistics nor a desire to secure any. It is full of examples that illustrate why it is the strength of relationships and not their statistical significance that mainly matters."
—Richard Lempert, Law and Social Inquiry
(Richard Lempert Law and Social Inquiry
"A clear trade-off: how much confidence [in a result] is "enough" depends on the costs of further research and the benefits of extra precision. Ziliak and his co-author Deirdre McCloskey argue in The Cult of Statistical Significance
that most academic disciplines have forgotten this trade-off . . . A sharp line for statistical significance makes no sense, and it has a cost."
—Tim Harford, The Financial Times
(Tim Harford Financial Times
"If not Fisherian significance, what should be the Holy Grail of statistics? Ziliak and McCloskey . . . answer: "Oomph." We should identify quantities that matter and measure them, not merely determine whether they can be distinguished from the null (meaning no effect) at some predetermined likelihood level. The validity of this point I take to be virtually self-evident. Yet statistical tests that ignore quantity remain pervasive, as the authors demonstrate through quantitative analyses of the contents of some very prestigious journals of economics, psychology, and medicine."
—Theodore Porter, Science
(Theodore Porter Science
"The book is a model of scholarship, transparent in its method, wide-reaching in its disciplinary expertise, and highly literate, including occasional haiku poems and humor such as, 'If the variable doesn't fit/you may not have to acquit.' The authors convincingly argue that environmental quality, jobs, and even lives are at stake."
—M. H. Maier, Glendale Community College, Choice
(M. H. Maier Choice
"What is important is a shift of emphasis away from a dichotomous world of true and false towards a recognition of "oomph". This is what the presented book tries to achieve. It is also fun to read, rich with historical information and an excellent reminder of what empirical work of any sort is all about."
—Walter Kramer, Stat Papers
(W. Kramer Stat Papers
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