Here we look at an important concept that is an extension from Bayes Theorem, which we discussed briefly.
The condition expectation identity says
The condition variance identity says
Here both and are both functions of Y and are therefore random variables themselves.
With this, we start by considering a random sum of random variables. Let where ‘s are IID with mean and variance , where is also a random variable, independent of ‘s.