In Bayesian theory, probability is a subjective measure that represents a degree-of-belief and is
always ‘conditional,’ which is contrary to the (objective) frequentist definition. The Bayesian view
consists of three stages that are essential to the process of inductive inference [50–52]:
1. Bayes’s theorem: If h stands for a hypothesis, d for a set of data, and I for background
(testable) information, then Bayes’s theorem states that: