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Duhem's Problem, the Bayesian Way, and Error Statistics, or “What's Belief Got to Do with It?”

Published online by Cambridge University Press:  01 April 2022

Deborah G. Mayo
Deborah G. Mayo*
Affiliation:
Department of Philosophy, Virginia Polytechnic Institute and State University
*
†Send reprint requests to the author, Department of Philosophy, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0126.
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Abstract

I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or “blamed” when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing auxiliary hypotheses from that of appraising a primary hypothesis. By discriminating patterns of error, this approach can at least block, if not also severely test, attempted explanations of an anomaly. I illustrate how this approach directs progress with Duhemian problems and explains how scientists actually grapple with them.

Information

Type
Research Article
Information
Philosophy of Science , Volume 64 , Issue 2 , June 1997, pp. 222 - 244
Copyright
Copyright © 1997 by the Philosophy of Science Association

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Footnotes

‡

I thank Philip Kitcher and an anomymous referee for extremely useful queries on a very early version of this paper. Variations on this paper have been presented at the University of Pittsburgh, Virginia Tech, The London School of Economics and Political Science, the University of Rochester, and the University of Minnesota. I benefited greatly from the questions and criticisms of all of these audiences.

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