of square feet of the house sqrift price =B + B,sqrift + u In a different Here are summary statistics for these variables. Variable | Obs Mean Std. Dev. Min Max price 289 95 . 1 42.5 26.0 300.0 sqrft 289 2103.0 695.3 735. 0 5136. 0 Equation 3 gives OLS estimates of the constant and slope coefficient for this model: (3) price, = 12.4+0.0393sqrft; A. What is the precise interpretation of the slope estimate, By ~0.039 ? B. Suppose that the variable " was changed by dividing by 100 so that this variable now represents square footage of the house, in hundreds of square feet. That is, suppose we issued the following commands in Stata gen sqrft_100 = sqrft/100 reg price sqrft_100 Given the information provided in this question only, is it possible to determine the numerical value of the slope and constant for this regression? If so, show how you determine them. If not, what is the minimum additional information that would be required to determine them? That is, is there anything short of having the entire data set and estimating another OLS regression that would allow you to determine the slope and constant in this regression? C. Suppose instead that we assumed a log-log functional form for the relationship between house sales price and square feet. Here are summary statistics for the variables in natural log units. summ Iprice Isqrft, format Variable Obs Mean Std. Dev. Min Max lprice 289 4.46 0 . 43 3.26 5. 70 Isqrft 289 7.60 0. 34 6. 60 8. 54 When we estimate the log-log model we obtain the following estimates