Prior odds ($O_{01}=\mathbb{P}(H_0)/\mathbb{P}(H_1)$)

For two exhaustive mutually exclusive models of positive prior probability, prior odds compare their probabilities before observing the data. They must be distinguished from the parameter prior distributions within those models. A Bayes factor multiplies these prior odds to produce posterior odds.