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 ( X₁ ) , the amount of insulation in inches ( X ₂ ) , the number of windows in the house ( X₃ ) , 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,when the builder used a simple linear regression model with house size (House) as the dependent variable and education (School) as the independent variable,he obtained an r² value of 23.0%.What additional percentage of the total variation in house size has been explained by including family size and income in the multiple regression?

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 ( X₁ ) , the amount of insulation in inches ( X ₂ ) , the number of windows in the house ( X₃ ) , 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,when the builder used a simple linear regression model with house size (House) as the dependent variable and education (School) as the independent variable,he obtained an r² value of 23.0%.What additional percentage of the total variation in house size has been explained by including family size and income in the multiple regression?

Quizplus · Accepted Answer

The Answer of 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,when the builder used a simple linear regression model with house size (House)as the dependent variable and education (School)as the independent variable,he obtained an r² value of 23.0%.What additional percentage of the total variation in house size has been explained by including family size and income in the multiple regression? A)2.8% B)51.8% C)72.6% D)74.8%

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