SCENARIO 14-4
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in hundreds of square feet and income is measured in thousands of dollars. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below:

Also SSR (X 1 | X 2 ) = 36400.6326 and SSR (X 1 | X 2 ) = 3297.7917
-Referring to Scenario 14-4,which of the following values for the level of significance is the smallest for which each explanatory variable is significant individually?
A)0.001
B)0.010
C)0.025
D)0.050

Question

SCENARIO 14-4
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in hundreds of square feet and income is measured in thousands of dollars. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below:

Also SSR (X 1 | X 2 ) = 36400.6326 and SSR (X 1 | X 2 ) = 3297.7917
-Referring to Scenario 14-4,which of the following values for the level of significance is the smallest for which each explanatory variable is significant individually?
A)0.001 
B)0.010 
C)0.025 
D)0.050

Quizplus · Accepted Answer

To determine the smallest level of significance for which each explanatory variable is significant individually, we need to look at the t-tests for the coefficients of the independent variables. From the Excel output, we can see that the t-values for both Income and Size are greater than the critical t-value at a significance level of 0.001 (column "P>|t|" in the output). Therefore, the smallest level of significance for which both explanatory variables are significant individually is 0.001.

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