Use the following output for Questions 1 5. A realtor built a regression model to explain the selling price of homes in a large Midwestern city. The variables are: PRICE The sales price is measured in thousands of dollars. For example, a value of home that sold for $269,000 will have a value of 269 in this dataset. SQFT The size of the living area in the house measured in thousands of square feet. For example, a home with 2,250 square feet will have a value of 2.25 in the dataset. BATH The number of bathrooms. ACREAGE The size of the lots measured in acres. The regression output is shown below: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept sqft bath acreage 0.919 0.844 0.834 32.5 Question 1 46 49 Coefficients 11.37 44.58 24.34 25.65 SS MS 2622522 87417.4 Question 2 1054.4 3107568 Standard Error t Stat 16.30 0.70 6.19 7.20 8.40 2.90 3.41 7.52 82.90 Pvaiae 0.4887 0.0000 0.0057 0.0000 Significance F 1.42053 E-18 Lower 95% -21.43 32.12 7.43 18.78 Upper 95% 44.17 57.05 41.25 32.52 Lt