Hey kingsolomonsgrave.
You won't be able to do that in general. Are these distributions joint Normal? If so do they have a covariance structure?
Remember that you stated Var[Ui|Xi=x] = sigma^2*Xi which is not in general equal to Var[Ui*Xi].
I am told that the variance of Ui given x is sigma squared times Xi and that the covariances between all ui is equal to sigma squared
if I want the variance of and I break it down so i have the variance of (from i=2 to n) I will end up having to compute
Can I take x out of the summation if the variance of u is dependent on x?
ie can I do this
Hey kingsolomonsgrave.
You won't be able to do that in general. Are these distributions joint Normal? If so do they have a covariance structure?
Remember that you stated Var[Ui|Xi=x] = sigma^2*Xi which is not in general equal to Var[Ui*Xi].