One of the most common questions of prospective house buyers pertains to the cos
ID: 3220438 • Letter: O
Question
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y). TTo provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X1) and the amount of insulation in inches (X2). Given below is EXCEL output of the regression model.
Q) What can we say about the regression model?
A) The model explains 27.78% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 19.28% of the sample variability of heating costs
B) The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 17.12% of the sample variability of heating costs
C) The model explains 17.12% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating costs
D) The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating costs
Regression Statistics Multiple R 0.5270 0.2778 R Square Adjusted R 0.1928 Square 40.9107 Standard Error Observations ANOVA SST df MS Significance F 10943.0190 5471.5095 3.2691 0.0629 Regression Residual 17 28452.6027 1673.6825 19 Total 39395.6218 Coefficients Standard Error t Stat P-value Lower 95% upper 95% 4.9379 0.0001 90.7853 Intercept 448.2925 256.7522 639.8328 1.2371 Temperature -2.7621 2.2327 0.0393 -5.3721 -0.1520 10.0638 5.2919 -1.5840 0.1316 -37.1736 Insulation -15.9408 Also, SSR(X1IX2) 8343.3572 and SSRO2IX1) 4199-2672Explanation / Answer
A) The model explains 27.78% of the variability of heating cost after correcting for the degrees of freedom, the model explains 19.28% of the sample variability of heating costs
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