Abstract

Among the many important contributions made by Wesley Salmon to the explication of the logic of hypothesis-appraisal has been his insistence that considerations additional to the inductive relations between evidence-statements and hypothesis may bear upon the probability of the latter. In particular, he has urged that the prior (to test) probability of a hypothesis H, as well as the likelihoods of H and not-#, must be taken into account in assessing the posterior (to test) probability value of H. Salmon has argued that the relationships among these several probability-values are captured by a particular interpretation of Bayes’ Theorem — a theorem of the formal probability calculus (Salmon [1967a], [1970c]). If this proposal is adopted, the problem arises of how to assign a value to the prior probability of H. Since no frequencies directly relevant to H will be available prior to initial testing, Salmon, who adopts a frequency interpretation of probability, must appeal to other considerations in estimating this prior probability value ([1967a], pp. 124 ff). These are what he calls “plausibility considerations” for H. As well as formal and pragmatic criteria, they include material criteria, such as considerations of simplicity and symmetry. From plausibility considerations of these various types, a scientist would be enabled to judge the plausibility of his/her hypothesis prior to test, and to estimate a prior probability value for insertion in Salmon’s Bayesian schema (ibid., pp. 115 ff, and my pp. 76–8 below). Even if, in many cases, the prior probability of a hypothesis is difficult to quantify precisely, Salmon’s recognition that this factor plays an important role in the appraisal of the hypothesis has always seemed to me to be a valuable insight.

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