ABSTRACT
Bayesians hold that belief is a matter of degree and can be represented in terms of probabilities. Thus p(E) is the probability I give to the statement E, which may range from 0, if I am certain E is false, to 1, if I am certain E is true. By representing beliefs as probabilities, it is possible to use the mathematical theory of probability to give an account of the dynamics of belief, and in particular an account of inductive confirmation. The natural thought is that evidence E supports hypothesis H just in case the discovery of E causes (or ought to cause) me to raise my degree of belief in H. To put the point in terms of probabilities, E supports H just in case the probability of H after E is known is higher than the probability of H beforehand. In the jargon, what is required is that the posterior probability of H be greater than its prior probability.
