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Error Statistics and Learning From Error: Making a Virtue of Necessity
Published online by Cambridge University Press: 01 April 2022
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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- Type
- Symposium: Philosophy of Statistics and Epistemology of Experiment: Bayesian vs. Error Statistical Approaches
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- Copyright © Philosophy of Science Association 1997
Footnotes
‡
I thank E. L. Lehmann for several important error statistical insights.
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