Variance, Invariance and Statistical Explanation

Erkenntnis 80 (S3):469-489 (2015)
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Abstract

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations

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Author's Profile

Denis Walsh
University of Toronto, St. George Campus

References found in this work

Depth: An Account of Scientific Explanation.Michael Strevens - 2008 - Cambridge, Mass.: Harvard University Press.
Explaining the brain: mechanisms and the mosaic unity of neuroscience.Carl F. Craver - 2007 - New York : Oxford University Press,: Oxford University Press, Clarendon Press.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.

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