Error statistics and learning from error: Making a virtue of necessity

Philosophy of Science 64 (4):212 (1997)
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Abstract

The error statistical account of testing uses statistical considerations, not to provide a measure of probability of hypotheses, but to model patterns of irregularity that are useful for controlling, distinguishing, and learning from errors. The aim of this paper is (1) to explain the main points of contrast between the error statistical and the subjective Bayesian approach and (2) to elucidate the key errors that underlie the central objection raised by Colin Howson at our PSA 96 Symposium

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2009-01-28

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Deborah Mayo
Virginia Tech

Citations of this work

Is frequentist testing vulnerable to the base-rate fallacy?Aris Spanos - 2010 - Philosophy of Science 77 (4):565-583.
Response to Howson and Laudan.Deborah G. Mayo - 1997 - Philosophy of Science 64 (2):323-333.
Error statistics and Duhem's problem.Gregory R. Wheeler - 2000 - Philosophy of Science 67 (3):410-420.

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References found in this work

Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
The self-vindication of the laboratory sciences.Ian Hacking - 1992 - In Andrew Pickering (ed.), Science as Practice and Culture. University of Chicago Press. pp. 29--64.
The Appraisal of Theories: Kuhn Meets Bayes.Wesley C. Salmon - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:325 - 332.

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