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Pearson's Wrong Turning: Against Statistical Measures of Causal Efficacy

Published online by Cambridge University Press:  01 January 2022

Robert Northcott
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Abstract

Standard statistical measures of strength of association, although pioneered by Pearson deliberately to be acausal, nowadays are routinely used to measure causal efficacy. But their acausal origins have left them ill suited to this latter purpose. I distinguish between two different conceptions of causal efficacy, and argue that: (1) Both conceptions can be useful; (2) The statistical measures only attempt to capture the first of them; (3) They are not fully successful even at this; (4) An alternative definition based more squarely on causal thinking not only captures the second conception, but also can capture the first one better too.

Type
Causality, Confirmation and Inference
Information
Philosophy of Science , Volume 72 , Issue 5: Proceedings of the 2004 Biennial Meeting of The Philosophy of Science Association. Part I: Contributed Papers , December 2005 , pp. 900 - 912
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

‡

I would like to thank Nancy Cartwright, and the audience at the Experimental Philosophy Laboratory at University of California, San Diego, for helpful comments on earlier versions of this paper.

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