Note that
\sigma is the paramter (not \sigma^2), but that
\sigma^2 is the
variance. Thus, we set \sigma, not \sigma^2.
I'm afraid I can't
distinuish these two.
In this case, when you set \sigma at srqt(2),
we get \sigma^2 of 2.
Exactly.
Don't
think about standard error or standard deviation at
all.
But don't we use standard error in solving (c)?
No. You should estimate sigma^2 according to the equation from
the section hand out. You cannot use the sd() function to
calculate sigma.
Also, in order to know how to calculate confidence
interval,
I read Rice's p. 538.
(Marc, this is where I mentioned!)
But I can't understand, in the proof of theorem B,
how he uses symmetry of X'X and XX'.
Does anybody give an idea?
Whenever I have doubts about matrix algebra, I refer to my handy
matrix algebra calculator (R). Try this in R:
Z <- matrix(1:12, nrow = 2, ncol = 6)
t(Z) %*% Z # Note that entry (i,j) is the same as entry (j,i)
for all i and j.
Z %*% t(Z) # Also symmetric!
Yours, Olivia