Bayesian statistics isn't just another method. It is an entirely alternative paradigm for practicing statistics. It uses probability models for making inferences, given the data that we have collected. This can be expressed in a fundamental expression as P(H|D).
Here, H is our hypothesis, that is, the thing we're trying to prove, and D is our data or observations.
As a reminder from our previous discussion, the diachronic form of Bayes' theorem is as follows:
Here, P(H) is an unconditional prior probability that represents what we know before we conduct our trial. P(D|H) is our likelihood function ...