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Real Estate Builder
a Real Estate Builder Wishes to Determine

question 24

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Real Estate Builder
A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below.
SUMMARY OUTPUT
 Regression Statistics  Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50\begin{array}{l}\text { Regression Statistics }\\\begin{array} { l l } \text { Multiple R } & 0.865 \\\text { R Square } & 0.748 \\\text { Adjusted R Square } & 0.726 \\\text { Standard Error } & 5.195 \\\text { Observations } & 50\end{array}\end{array} ANOVA
 Real Estate Builder A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT   \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l l }  \text { Multiple R } & 0.865 \\ \text { R Square } & 0.748 \\ \text { Adjusted R Square } & 0.726 \\ \text { Standard Error } & 5.195 \\ \text { Observations } & 50 \end{array} \end{array}  ANOVA     \begin{array} { | l | c c c c | }  \hline & \text { Coeff } & \text { St. Error } & \boldsymbol { t }\boldsymbol {Sat } & \boldsymbol { P } \text {-value } \\ \hline \text { Intercept } & - 1.6335 & 5.807 \mathrm { 8 } & - 0.281 & 0 .7798 \\ \text { Family Incame } & 0.4485 & 0.1137 & 3.9545 & 0 .0003 \\ \text { Family Size } & 4.2615 & 0.8062 & 5.286 & 0 .0001 \\ \text { Education } & - 0.6517 & 0.4319 & - 1.509 & 0 .1383 \\ \hline \end{array}  -{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which at least two explanatory variables are significant individually:  \alpha  = .01,.05,.10,and .15?  Coeff  St. Error tSatP-value  Intercept 1.63355.80780.2810.7798 Family Incame 0.44850.11373.95450.0003 Family Size 4.26150.80625.2860.0001 Education 0.65170.43191.5090.1383\begin{array} { | l | c c c c | } \hline & \text { Coeff } & \text { St. Error } & \boldsymbol { t }\boldsymbol {Sat } & \boldsymbol { P } \text {-value } \\\hline \text { Intercept } & - 1.6335 & 5.807 \mathrm { 8 } & - 0.281 & 0 .7798 \\\text { Family Incame } & 0.4485 & 0.1137 & 3.9545 & 0 .0003 \\\text { Family Size } & 4.2615 & 0.8062 & 5.286 & 0 .0001 \\\text { Education } & - 0.6517 & 0.4319 & - 1.509 & 0 .1383 \\\hline\end{array}
-{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which at least two explanatory variables are significant individually: α\alpha = .01,.05,.10,and .15?


Definitions:

Price/demand Elasticity

A measure of how much the demand for a product changes in response to a change in its price.

Continuous Values

Numerical data that can take any value within a specified range, often associated with measurements.

Production Cost

The total expense incurred in the manufacturing of a product or providing a service, including raw materials, labor, and overhead costs.

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