Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability of a hypothesis as more evidence or information becomes available. It contrasts with frequentist methods, which do not incorporate prior knowledge. The core idea is to combine prior probability distributions with likelihood functions derived from current data to produce posterior probabilities.
