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

question 18

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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.
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<sub>1</sub> ) , the amount of insulation in inches ( X <sub>2</sub> ) , the number of windows in the house ( X<sub>3</sub> ) , and the age of the furnace in years ( X <sub>4</sub> ) . 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 r<sup>2</sup> 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 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<sub>1</sub> ) , the amount of insulation in inches ( X <sub>2</sub> ) , the number of windows in the house ( X<sub>3</sub> ) , and the age of the furnace in years ( X <sub>4</sub> ) . 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 r<sup>2</sup> 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%
-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?

Comprehend the principles of practical versus perfection standards and their implications on cost variances.
Grasp the concept of labour efficiency variance and its relevance in manufacturing processes.
Learn the method of calculating direct labour and material costs in standard costing.
Understand the impact of actual cost variations from standard costs on cost accounting.

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A perspective in psychology that emphasizes the purposes of behavior and mental processes and how they adapt to the environment.

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