It can be shown using variable transformations that if Q1(1,) and Q2(2,) are independent then Q1+Q2 and Q1+Q2Q1 are independent random variables with distributions (1+2,) and beta (1,2) respectively. Apply this result to the simple regression model yi=0+1xi+i,i=1,,n. The Gauss-Markov conditions hold and also iN(0,). Note: You will need to find Q1 and Q2 which are functions of the estimates that match the statement above. Provide two examples. It can be shown using variable transformations that if Q1(1,) and Q2(2,) are independent then Q1+Q2 and Q1+Q2Q1 are independent random variables with distributions (1+2,) and beta (1,2) respectively. Apply this result to the simple regression model yi=0+1xi+i,i=1,,n. The Gauss-Markov conditions hold and also iN(0,). Note: You will need to find Q1 and Q2 which are functions of the estimates that match the statement above. Provide two examples