Is there life after P<0.05? Statistical significance and quantitative sociology

Is there life after P<0.05? Statistical significance and quantitative sociology The overwhelming majority of quantitative work in sociology reports levels of statistical significance. Often, significance is reported with little or no discussion of what it actually entails philosophically, and this can be problematic when analyses are interpreted. Often, significance is understood to represent the probability of the null hypothesis (usually understood as a lack of relationship between two or more variables). This understanding is simply erroneous. The first section of this paper deals with this common misunderstanding. The second section gives a history of significance testing in the social sciences, with reference to the historical foundations of many common misinterpretations of significance testing. The third section is devoted to a discussion of the consequences of misinterpreting statistical significance for sociology. It is argued that reporting statistical significance provides sociology with very little value, and that the consequences of misinterpreting significance values outweighs the benefits of their use. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Is there life after P<0.05? Statistical significance and quantitative sociology

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Publisher
Springer Netherlands
Copyright
Copyright © 2011 by Springer Science+Business Media B.V.
Subject
Social Sciences, general; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-011-9516-z
Publisher site
See Article on Publisher Site

Abstract

The overwhelming majority of quantitative work in sociology reports levels of statistical significance. Often, significance is reported with little or no discussion of what it actually entails philosophically, and this can be problematic when analyses are interpreted. Often, significance is understood to represent the probability of the null hypothesis (usually understood as a lack of relationship between two or more variables). This understanding is simply erroneous. The first section of this paper deals with this common misunderstanding. The second section gives a history of significance testing in the social sciences, with reference to the historical foundations of many common misinterpretations of significance testing. The third section is devoted to a discussion of the consequences of misinterpreting statistical significance for sociology. It is argued that reporting statistical significance provides sociology with very little value, and that the consequences of misinterpreting significance values outweighs the benefits of their use.

Journal

Quality & QuantitySpringer Journals

Published: Jun 1, 2011

References

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