How Probabilities Reflect Evidence

Many philosophers think of Bayesianism as a theory of practical rationality. This is not at all surprising given that the view’s most striking successes have come in decision theory. Ramsey (1931), Savage (1972), and De Finetti (1964) showed how to interpret subjective degrees of belief in terms of betting behavior, and how to derive the central probabilistic requirement of coherence from reflections on the nature of rational choice. This focus on decision-making can obscure the fact that Bayesianism is also an epistemology. Indeed, the great statistician Harold Jeffries (1939), who did more than anyone else to further Bayesian methods, paid rather little heed to the work of Ramsey, de Finetti, and Savage. Jeffries, and those who followed him, saw Bayesianism as a theory of inductive evidence, whose primary role was not to help people make wise choices, but to facilitate sound scientific reasoning. This paper seeks to promote a broadly Bayesian approach to epistemology by showing how certain central questions about the nature of evidence can be addressed using the apparatus of subjective probability theory. Epistemic Bayesianism, as understood here, is the view that evidential relationships are best represented probabilistically. It has three central components: