(b) Consider a linear regression model which can be written as: Yi = Bi +e where the B1 is the intercept parameter and e is the IID random error term. Let Bi be the OLS estimator of B1, and let i denote the number of observation, i = 1, ...,N. (i) Show that Bi = , that is, the sample average is the estimator. [4] (ii) Show that the residual terms always sum to zero. [2] (b) Consider a linear regression model which can be written as: Yi = Bi +e where the B1 is the intercept parameter and e is the IID random error term. Let Bi be the OLS estimator of B1, and let i denote the number of observation, i = 1, ...,N. (i) Show that Bi = , that is, the sample average is the estimator. [4] (ii) Show that the residual terms always sum to zero. [2]