- #1
jimmy1
- 61
- 0
I have 2 normally distributed dependent random variables, X and Y, and I have the mean and variance of both of them, and I want to find the covariance (or correlation) between X and Y.
Now the formula for the covariance is Cov(XY) = E(XY) - E(X)E(Y). So I tried to calculate E(XY) via the bivariate normal distribution, but it seems that to use the bivariate normal I need to provide the correlation coefficent as a parameter, but this is the parameter that I'm trying to actually find.
So how would I find an expression for the covariance of X and Y? To find E(XY), it seems you need to use P(XY), but to use this bivariate probability you need to provide the covariance (or correlation coefficent). So how do I get around this problem??
Now the formula for the covariance is Cov(XY) = E(XY) - E(X)E(Y). So I tried to calculate E(XY) via the bivariate normal distribution, but it seems that to use the bivariate normal I need to provide the correlation coefficent as a parameter, but this is the parameter that I'm trying to actually find.
So how would I find an expression for the covariance of X and Y? To find E(XY), it seems you need to use P(XY), but to use this bivariate probability you need to provide the covariance (or correlation coefficent). So how do I get around this problem??