Q2. [22 points] Suppose we have the following linear regression model with p predictors: Yi = Bo+ Bic1,it .. . + BpXpi + Ei (i = 1, . .. , n) where Ei ~N(0, 02). In lecture 13, we partitioned the sum of squares, as follows: n n n [( Yi - Y)2 = + [(x - Y)2 i=1 i=1 i=1 Total Sum of Squares (SST) Error Sum of Squares (SSE) Regression Sum of Squares (SSR)