This is a stupid question, but is this the formula to calculate the covariance matrix? X'X? or is it the inverse of that?
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the inverse of X'X is the variance-covariance matrix of the parameter estimates
I'm guessing what is being asked here is... $\displaystyle V(\hat\beta)=\sigma^2(X^tX)^{-1}$ for the classical linear model.
yeahh well actually the question in my homework was actually what is the use of X'X? so i was just confirming it that could become the variance covariance matrix so i have something to say. but thanks guys
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