What is Bayesian Analysis?
The paradigm of Bayesian analysis can be summarized as: For each possible explanation of the sample, count all the ways the sample could happen, explanations with more ways to produce the sample are more plausible.
In Bayesian statistics, plausibility of the explanations is called posterior:
$\underbrace {f(\theta|data)}{posterior} =\underbrace {f(data|\theta)}{likelihood}\underbrace{f(\theta)}{prior}/\underbrace{f(data)}{marginal\likelihood}$