5.13 Suppose (Yi,Xi) satisfy the least squares assumptions in Key Concept 4.3 and, in addition, ui is distributed N(0,u2) and is independent of Xi. a. Is ^1 conditionally unbiased? assion with a Single Regressor: Hypothesis Tests and Confidence Intervals b. Is ^1 the best linear conditionally unbiased estimator of 1 ? c. How would your answers to (a) and (b) change if you assumed only that (Yi,Xi) satisfied the least squares assumptions in Key Concept 4.3 and var(uiXi=x) is constant? d. How would your answers to (a) and (b) change if you assumed only that (Yi,Xi) satisfied the least squares assumptions in Key Concept 4.3? 5.13 Suppose (Yi,Xi) satisfy the least squares assumptions in Key Concept 4.3 and, in addition, ui is distributed N(0,u2) and is independent of Xi. a. Is ^1 conditionally unbiased? assion with a Single Regressor: Hypothesis Tests and Confidence Intervals b. Is ^1 the best linear conditionally unbiased estimator of 1 ? c. How would your answers to (a) and (b) change if you assumed only that (Yi,Xi) satisfied the least squares assumptions in Key Concept 4.3 and var(uiXi=x) is constant? d. How would your answers to (a) and (b) change if you assumed only that (Yi,Xi) satisfied the least squares assumptions in Key Concept 4.3