Hi, I was wondering how E[PD^2] = p = E[PD] holds true, is it by definition? Thanks in advance!
I could not find a thread related to this when searching for one.
the original text is sloppy. PD is here a random variable that can be 1 or 0. The probability of PD being one is p.
Expected value of PD:
E[PD] = p * 1 + (1-p) * 0 = p
Expected value of PD^2:
E[PD^2] = p * 1^2 + (1-p) * 0^2 = p
it follows that E[PD] = E[PD^2] = p
Which is a property of the Bernoulli distribution. I’m not sure it’s unique to it, but for most distributions it is not true.
This site uses cookies to help personalise content, tailor your experience and to keep you logged in if you register.
By continuing to use this site, you are consenting to our use of cookies.