MLR.5, homoskedasticity, is the key assumption needed to show that the estimators β0ˆ, β1ˆ, . . . , βkˆhave...? {Ans: The smallest variance}True or false: If two regressions use different sets of observations, then we can tell how the R-squareds will compare, even if one regression uses a subset of regressors. {Ans: False}Which of the following is true of BLUE? a. It is a rule that can be applied to any one value of the data to produce an estimate. b. An estimator is linear if and only if it can be expressed as a linear function of the data on the dependent variable. c. It is the best linear uniform estimator. {Ans: b}Exclusion of a relevant variable from a multiple linear regression model leads to the problem of: a. misspecification of the model b. homoskedasticity c. perfect collinearity d. multicollinearity {Ans: a}True or False: True or False: Assuming you use the exact same data set as before, adding the explanatory variable bmi will always decrease the R2 {Ans: False}Which of the following is true of R^2? a. R^2shows what percentage of the total variation in the dependent variable, Y, is explained by the explanatory