During your derivation, I recommend leaving the residual sum of squares written asR S S RSS, rather than writing it out as? ( y i ? ( ? ^ 0 + ? ^ 1 x i ) ) 2 ?(yi ??(? ^ ?0 ?+? ^ ?1 ?xi ?))2.

In lecture, we showed that the estimates of from 0L5 are also the maximum likelihood estimates. For a simple linear regrssion model, show that the MLE of U2 is proportional to (but not identical to) the estimate of 02 from OLS. During your derivation, | recommend leaving the residual sum of squares written as RSS, rather than writing it out as E (y,- (g + ling