SCENARIO 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y). To 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 ( X 1 ) and the amount of insulation in inches ( X 2 ). Given below is EXCEL output of the regression model.

Also SSR (X 1 | X 2 ) = 8343.3572 and SSR (X 2 | X 1 ) = 4199.2672
-Referring to Scenario 14-6,what can we say about the regression model?
A)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.
B)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.
C)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.
D)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.

Question

SCENARIO 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y). To 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 ( X 1 ) and the amount of insulation in inches ( X 2 ). Given below is EXCEL output of the regression model.

Also SSR (X 1 | X 2 ) = 8343.3572 and SSR (X 2 | X 1 ) = 4199.2672
-Referring to Scenario 14-6,what can we say about the regression model?
A)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. 
B)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. 
C)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. 
D)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.

Quizplus · Accepted Answer

The Answer of SCENARIO 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y). To 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 ( X 1 ) and the amount of insulation in inches ( X 2 ). Given below is EXCEL output of the regression model.

Also SSR (X 1 | X 2 ) = 8343.3572 and SSR (X 2 | X 1 ) = 4199.2672
-Referring to Scenario 14-6,what can we say about the regression model?
A)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. 
B)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. 
C)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. 
D)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.

SCENARIO 14-6 One of the Most Common Questions of Prospective House Buyers