\fData and context for Questions 1, 2 and 3 You will use the data le br5 available in csv and Eviews format (.wfl) on Moodle to answer these question. The data provides prices and characteristics of a sample of houses. The variables are as follows: 0 price: Selling price in thousand dollars 0 baths: Number of bathrooms 0 bedrooms: Number of bedrooms 0 sqft: Total living area (total size) of the house in hundreds of square feet I age: age of each house in years View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: PRICE Method: Least Squares Date: 09/28/21 Time: 14:06 Sample: 1 900 Included observations: 900 Variable Coefficient Std. Error t-Statistic Prob. C -62.46140 9. 182401 -6.802295 0.0000 SQFT 7.916557 0.348160 22.73831 0.0000 AGE -0.577210 0. 138497 -4. 167680 0.0000 BATHS 23.13072 5.660916 4.086038 0.0000 R-squared 0.629735 Mean dependent var 151.2452 Adjusted R-squared 0.628495 S.D. dependent var 111.4407 S.E. of regression 67.92448 Akaike info criterion 11.27910 Sum squared resid 4133906. Schwarz criterion 11.30045 Log likelihood -5071.597 Hannan-Quinn criter. 11.28726 F-statistic 507.9623 Durbin-Watson stat 1.979329 Prob(F-statistic) 0.000000