It is seldom, if ever, the case that there is one piece of science that provides a definitive answer to a particular resource management issue. It is far more likely that we would want to weigh the cumulative evidence to understand the consequences of a given resource management decision. Bayesian statistics, and the corresponding inference, is a quantitative tool that, by its very nature, enables incorporating previous evidence and knowledge, along with newly acquired data, to estimate the probability of a particular outcome. Although the mathematics are beyond these introductory comments, Bayes’ Theorem essentially works to produces the probability distribution of an outcome, using (1) the cumulative existing knowledge, described in the form of a prior probability distribution, (2) the likelihood of existing data, given the prior probability distribution, and (3) a constant.