Spring is a peak time for selling houses. The file Spring Houses contains the selling price, number of bathrooms, square footage, and number of bedrooms of homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor. com website) Click on the datafile logo to reference the data. DATA file a. The Excel output for the estimated regression equation that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house: SUMMARY OUTPUT Regression statistics Multiple R 0.7429 R Square 0.5519 Adjusted R Square 0.4907 Standard Error 61948.6931 Observations 26 ANOVA dr SS 1.0397E+11 8.4428E+10 1.8840E+11 Regression Residual Total 9.0306E+00 MS 3.4656E+10 3.8376E+09 Significance F 4.3455E-04 3 22 25 Intercept Baths Sq Ft Beds Coeficients Standard Error -5531.0144 67312.9506 -1386.2100 23143.8052 60.2793 23.6813 4787077 3401.7K02 Star -0.0822 -0.0599 2.5562 2.3813 P-value Lower 959 Upper 95% 0.9353-145129.5298 134067.5011 0.9528 -19383.5243 46611 1014 0.0180 11.3748 109.1838 002 4L141104611.0095 Does the estimated regression equation provide a good fit to the data? Explain. Hints if is greater than 43%, the estimated regression equation good fit. The estimated regression equation - Select your answer provide a reasonable fit because the adjusted Ris (to 2 decimals). b. The Excel output for the estimated regression equation that can be used to predict selling price given square footage and the number of bedrooms: SUMMARY OUTPUT Regression statistics Multiple R 0.7428 R Square 0.5518 Adjusted R Square 0.5128 Standard Error 60591.9567 Observations 26 ANOVA dr Significance F 9.81929E-05 SS 2 1.03965E+11 23 84441860122 25 1.88396E+11 MS 51977265516 3671385223 Regression Residual Total 14.15739901 Intercept Sq Ft Beds Coefficients -5882.7622 69.7331 54309.2083 Standard Error 65587.6835 21.2707 22101.6231 Stat -0.0897 2.8082 2.4572 P-value Lower 95% 0.9293-141561.2229 0.0100 15.7313 0.0220 8588.5174 Upper 95% 129795.6985 103.7349 100029.8991 Compare the fit for this simpler model to that of the model that also includes number of bathrooms as an independent variable The adjusted for the simpler model is (to 2 decimals) that is Select your answer than the adjusted R of the model in part a.