SCENARIO 18-2
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 Scenario 18-1,at the 0.01 level of significance,what conclusion should the builder reach regarding the inclusion of Income in the regression model?
A)Income is significant in explaining house size and should be included in the model because its p-value is less than 0.01.
B)Income is significant in explaining house size and should be included in the model because its p-value is more than 0.01.
C)Income is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01.
D)Income is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.

Question

SCENARIO 18-2
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 Scenario 18-1,at the 0.01 level of significance,what conclusion should the builder reach regarding the inclusion of Income in the regression model?
A)Income is significant in explaining house size and should be included in the model because its p-value is less than 0.01. 
B)Income is significant in explaining house size and should be included in the model because its p-value is more than 0.01. 
C)Income is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01. 
D)Income is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.

Quizplus · Accepted Answer

Income is significant in explaining house size and should be included in the model if its p-value is less than 0.01, indicating a strong statistical significance at the 0.01 level of significance.

SCENARIO 18-2 One of the Most Common Questions of Prospective House Buyers