17) The Degrees of freedom for the sum of squares regression are 98, 3, 99, or 4?18) The number of homes that were included in this sample is 99, 100, 98, or 4?22) the degrees of freedom for the sum of squares error are 99, 95, 98, or 4?24) The p value for the hypothesis test for the overall regression model is 1.654, 0.000, 0.165 or 0.052?25) the critical value(s) to test the significance of the regression coefficients using a=0.05 are a) -1.661, 1.661b) -2.000, 2.000c) -1.654, 1.654d) -1.985, 1.985

A home appraisal company would like to develop a regression model that would predict the selling price of a house based on the age of the blouse in years (Age), the living area of the house in square feet (Living Area), the number of bedrooms (Bedrooms), and the number of bathrooms (Bathrooms). The following Excel output shows the partially completed regression output from a random sample of homes that have recently sold. SUMMARY OUTPUT Regression Statistics Multiple R [1922986098 R Square Adjusted R Square Standard Emir 96.01662486 Observations ANOVA cf! 55 MS F Signicance F Regression 5,038,038.98 136.6182318 1.65419E-38 Residual ' Total 99 5,913,862.24 Co ejcien ts Standard Error t Stat Pvalue to war 95% Upper 95% Intercept 171.33.343.74 8100155442 0.051830132 Bedrooms 7126216484 21.63115883 0.000558736 Age -6.083537657 1.73017584 0.000673135 Living Area 0.154332701 0019897358 9.78074E-12 Bathrooms 6319037185 20.44224613 0.757909773