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

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Authors: Stephen Thomas Ziliak, Deirdre N. Mccloskey
Publisher: University of Michigan Press
Category: Book

List Price: ~~Ł17.50~~
Buy New: Ł7.97
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New (21) Used (7) from Ł6.99

Rating: 4.0 out of 5 stars

1 reviews
Sales Rank: 194707

Media: Paperback
Number Of Items: 1
Pages: 352
Shipping Weight (lbs): 1
Dimensions (in): 9 x 5.9 x 1

ISBN: 0472050079
Dewey Decimal Number: 330.015195
EAN: 9780472050079
ASIN: 0472050079

Publication Date: January 15, 2008
Availability: Usually dispatched within 1-2 business days
Shipping: International shipping available
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•	Hardcover - The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (Economics, Cognition & Society): How the Standard Error ... and Lives (Economics, Cognition & Society)

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Customer Reviews:

4 out of 5 stars

Bring back effect sizes March 14, 2008
4 out of 4 found this review helpful

This book shows how many scientific disciplines rely way too much on the concept of statistical significance. I have read the book and I find it convincing. The authors show how the focus on statistical significance has taken away attention for 'real' significance. In other words: the focus on statistical significance often means that researchers fail to ask whether their findings matter. In statistics, a result is called statistically significant if it is unlikely to have occurred by chance. So testing for statistical significance is asking the question how likely it is that an effect exists. It does not answer at all how strong and important this effect is. And this latter question about the effect size is much more important from a scientific and a practical perspective. Statistical significance does not imply an effect is important, lack of statistical significance does not mean an effect is not important. Mind you the book is NOT a plea against quantitative research nor statistical analysis. On the contrary. It is a plea for doing it and doing it right by bringing back focus on effect sizes in social science.