TABLE 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 Table 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

TABLE 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 Table 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 TABLE 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 Table 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.

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