## § Conditional probability is neither causal nor temporal

I found this insightful:
`P(A|B)`

means the probability of A happening given B already happened. Not so! `P(A|B)`

doesn’t specify the time ordering of A and B. It specifies the order in which YOU learn about them happening. So P(A|B) is the probability of A given you know what happened with B.

This makes sense from the information theoretic perspective; I'd never meditated
on this difference, though.
I'd seen things like:
`P(sunrise | rooster-crow) = large`

even though rooster crowing does not *cause* the sunrise to happen.

but I'd never seen/actively contemplated an example of `P(A|B)`

where they
are temporally reversed/ambiguous.