TABLE 17-2
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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X 1 ),the amount of insulation in inches (X 2 ),the number of windows in the house (X 3 ),and the age of the furnace in years (X 4 ).Given below are the EXCEL outputs of two regression models.
-Referring to Table 17-2,what can we say about Model 1?
A)The model explains 77.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.1% of the sample variability of heating costs.
B)The model explains 75.1% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 77.7% of the sample variability of heating costs.
C)The model explains 80.8% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.7% of the sample variability of heating costs.
D)The model explains 75.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 80.8% of the sample variability of heating costs.

Question

TABLE 17-2
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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X 1 ),the amount of insulation in inches (X 2 ),the number of windows in the house (X 3 ),and the age of the furnace in years (X 4 ).Given below are the EXCEL outputs of two regression models.  
-Referring to Table 17-2,what can we say about Model 1?
A)The model explains 77.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.1% of the sample variability of heating costs. 
B)The model explains 75.1% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 77.7% of the sample variability of heating costs. 
C)The model explains 80.8% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.7% of the sample variability of heating costs. 
D)The model explains 75.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 80.8% of the sample variability of heating costs.

Quizplus · Accepted Answer

The Answer of TABLE 17-2
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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X 1 ),the amount of insulation in inches (X 2 ),the number of windows in the house (X 3 ),and the age of the furnace in years (X 4 ).Given below are the EXCEL outputs of two regression models.  
-Referring to Table 17-2,what can we say about Model 1?
A)The model explains 77.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.1% of the sample variability of heating costs. 
B)The model explains 75.1% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 77.7% of the sample variability of heating costs. 
C)The model explains 80.8% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 75.7% of the sample variability of heating costs. 
D)The model explains 75.7% of the sample variability of heating costs; after correcting for the degrees of freedom,the model explains 80.8% of the sample variability of heating costs.

TABLE 17-2 One of the Most Common Questions of Prospective House Buyers