Causal Interpretations of Probability
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The prospects of a causal interpretation of probability are examined. Various accounts both from the history of scientific method and from recent developments in the tradition of the method of arbitrary functions, in particular by Strevens, Rosenthal, and Abrams, are briefly introduced and assessed. I then present a specific account of causal probability with the following features: (i) First, the link between causal probability and a particular account of induction and causation is established, namely eliminative induction and the related difference-making account of causation in the tradition of Bacon, Herschel, and Mill. (ii) Second, it is shown how a causal approach is useful beyond applications of the method of arbitrary functions and is able to deal with various shades of both ontic and epistemic probabilities. (iii) Furthermore, I clarify the notion of causal symmetry as a central element of an objective version of the principle of indifference and relate probabilistic independence to causal irrelevance. According to the proposed account, probability distributions are interpreted in terms of causal symmetries in the circumstances rather than relative frequencies.