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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, at the 0.01 level of significance, what conclusion should the builder draw 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. 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, at the 0.01 level of significance, what conclusion should the builder draw 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. 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, at the 0.01 level of significance, what conclusion should the builder draw 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.
-Referring to Table 14-4, at the 0.01 level of significance, what conclusion should the builder draw 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.

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