- Recall the normality assumption for the regression model: yi = x; B+ ei i = 1, . .., n, with E; ~ N(0, 62) - This implies that y ~ Nn (XB, 621). - We can show that the likelihood function can be written as: RSS N= L( B, 02 ly) x n - The value of B that maximizes the Likelihood function is the Maximum Likelihood Estimator (MLE) of B. - This estimator is equal to the LS estimate of B