In Bayes' theorem, what is little $p$?

Question

In Wikipedia's conjugate prior article, Bayes theorem is given as:

$$p(\theta|x) = \frac{p(x|\theta) \, p(\theta)} {\int p(x|\theta') \, p(\theta') \, d\theta'}.$$

What is $p$ here? Is it the density for continuous distributions and the probability mass function for discrete distributions?

Answer 1

$p(A|B)$ means the probability of A being true given the assumed truth of B; “AB” means “A and B”, etc. This basically follows from the fact that “A and B” must always be equivalent to “B and A”.