Comments and Criticism: Measuring Confirmation and Evidence

Journal of Philosophy 97 (12):663-672 (2000)
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Abstract

Bayesian epistemology suggests various ways of measuring the support that a piece of evidence provides a hypothesis. Such measures are defined in terms of a subjective probability assignment, pr, over propositions entertained by an agent. The most standard measure (where “H” stands for “hypothesis” and “E” stands for “evidence”) is: the difference measure: d(H,E) = pr(H/E) - pr(H).0 This may be called a “positive (probabilistic) relevance measure” of confirmation, since, according to it, a piece of evidence E qualitatively confirms a hypothesis H if and only if pr(H/E) > pr(H), where qualitative disconfirmation is characterized by replacing “>” with “ “ with “=”. Other more or less standard positive relevance measures that have been proposed are: the log-ratio measure: r(H,E) = log[pr(H/E)/pr(H)] and the log-likelihood-ratio measure: l(H,E) = log[pr(E/H)/pr(E/~H)].

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Branden Fitelson
Northeastern University

References found in this work

Symmetries and asymmetries in evidential support.Ellery Eells & Branden Fitelson - 2002 - Philosophical Studies 107 (2):129 - 142.
Problems of Old Evidence†.Ellery Eells - 2017 - Pacific Philosophical Quarterly 66 (3-4):283-302.

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