You estimated the following linear regression model that predicts house prices. SUMMARY OUTPUT Regression Statistics Multiple R 0.96 R Square 0.92 Adjusted R Square 0.91 Standard Error 12243.45 Observations 150 Coefficients Standard Error Stat P-value Lower 95% Upper 95% Intercept 89927.54 5482.23 16.40 0.0 79090.21 100764.87 33.58 3.66 9.18 0.00 26.35 10.81 House Size Lot Size 7912.08 455.96 17.35 0.00 7010.73 8813.44 1544.25 1207.58 -1.28 0.20 3931.41 842.91 Bedrooms Bathrooms 16134.98 2237.89 7.21 0.00 11710.89 20559.06 Lake 37157.34 2038.56 18.23 33127.50 41187.19 16887.66 2367.83 0.00 21568.41 12206.92 Driveway -7.13 Street 30647.52 2806.17 -10.92 0.00 36194.78 -25100.25 The variable information is the following: Variable Comment House Price in dollars House Size in square feet Lot Size in acres Bedrooms number of bedrooms Bathrooms number of bathrooms Lakeview Yes/No: whether or not house has a lakeview Parking Type "Street Parking", "Driveway Parking", "Garage Parking" What percent of the variation in house prices is explained by the variation in all the independent variables? Please answer to 2 decimal places. (For example, if the correct answer is 53%, you need to enter 0.53)