Two independent events
$$
\newcommand{\bP}{\mathbb{P}}
$$
We say that two events, \(A\) and \(B\), are independent when learning that \(A\) has occurred does not change your probability that \(B\) occurs. That is, \(\bP(B \mid A) = \bP(B)\). Equivalently, \(A\) and \(B\) are independent if \(\bP(A)\) doesn’t change if you condition on \(B\): \(\bP(A \mid B) = \bP(A)\).
Another way to state independence is that \(\bP(A,B) = \bP(A) \bP(B)\).
All these definitions are equivalent:
$$\bP(A,B) = \bP(A)\; \bP(B \mid A)$$
by the chain rule, so
$$\bP(A,B) = \bP(A)\; \bP(B)\;\; \Leftrightarrow \;\; \bP(A)\; \bP(B \mid A) = \bP(A)\; \bP(B) \ ,$$
and similarly for \(\bP(B)\; \bP(A \mid B)\).
Children:
Parents:
- Probability theory
The logic of science; coherence relations on quantitative degrees of belief.
I’m not sure what this equation is trying to tell me. Some parts of it are only true if A and B are independent, but some parts are true in general, right?
Yeah this is maybe a placeholder to support the lens, added stub tag.