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TABLE 14-4 A Real Estate Builder Wishes to Determine How House Size

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TABLE 14-4
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) , family size (Size) , and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below:
SUMMARY OUTPUT
Regression Statistics
TABLE 14-4 A real estate builder wishes to determine how house size (House)  is influenced by family income (Income) , family size (Size) , and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below: SUMMARY OUTPUT Regression Statistics    ANOVA      -Referring to Table 14-4, 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% ANOVA
TABLE 14-4 A real estate builder wishes to determine how house size (House)  is influenced by family income (Income) , family size (Size) , and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below: SUMMARY OUTPUT Regression Statistics    ANOVA      -Referring to Table 14-4, 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% TABLE 14-4 A real estate builder wishes to determine how house size (House)  is influenced by family income (Income) , family size (Size) , and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below: SUMMARY OUTPUT Regression Statistics    ANOVA      -Referring to Table 14-4, 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 Table 14-4, 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?


Definitions:

Scatterplot

A graphical representation using dots to show the relationship between two quantitative variables.

Variables

Elements or characteristics within a study or research that can change and potentially impact the study's results.

Negative Correlation

A relationship between two variables whereby they move in opposite directions.

Direct Correlation

A relationship between two variables where an increase in one variable is associated with an increase in the other, or a decrease in one is associated with a decrease in the other.

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