Bayesians assess the inductive support for theoretical hypotheses on the basis of two sorts of factors, one fairly objective, the other highly subjective. The objective factor consists of the likelihoods or direct inference probabilities that theoretical hypotheses specify for evidential events. This is the means by which evidence affects inductive support. The subjective factor consists of the prior probabilities assigned to the various competing hypotheses. For a Bayesian agent the prior probability of a hypothesis represents how plausible the agent considers the hypothesis to be before the impact of evidence is considered, and Bayesian agents may radically differ in their initial plausibility assessments. Bayes’ formula combines likelihoods with an agent's prior probabilities to produce the agent's posterior probability for each hypothesis. Posterior probabilities represent how plausible an agent considers the hypothesis to be after the evidence is taken into account.