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TABLE 14-4
a Real Estate Builder Wishes to Determine How

question 22

Multiple Choice

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:
 Regression Stuistics  Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50\begin{array}{ll} & \text { Regression Stuistics } \\\hline \text { Multiple R } & 0.865 \\\text { R Square } & 0.748 \\\text { Adjusted R Square } & 0.726 \\\text { Standard Error } & 5.195 \\\text { Observations } &50 \\\hline\end{array}
ANOVA
 d f S S M S Significance F Regression3605.77361201.92450.0000Residual1214.226426.3962Total494820.0000\begin{array}{lrrrrr}\hline & \text { d f }& \text {S S } & \text {M S } & \text {F } & \text {Significance F } \\\hline \text {Regression} & & 3605.7736 & 1201.9245 & &0.0000 \\\text {Residual} & & 1214.2264 & 26.3962 & \\Total & 49 & 4820.0000 & & & \\\hline\end{array}

 CoefficientsStandard Errort Stat p -valueIntercept 1.63355.80780.2810.7798Income0.44850.11373.95450.0003Size4.26150.80625.2860.0001School 0.65170.43191.5090.1383\begin{array}{lcccc}\hline & \text { Coefficients} & \text {Standard Error} & \text {t Stat }& \text {p -value} \\\hline \text {Intercept }& -1.6335 & 5.8078 & -0.281 & 0.7798 \\ \text {Income} & 0.4485 & 0.1137 & 3.9545 & 0.0003 \\ \text {Size} & 4.2615 & 0.8062 & 5.286 & 0.0001 \\ \text {School }& -0.6517 & 0.4319 & -1.509 & 0.1383 \\\hline\end{array}

-Referring to Table 14-4, at the 0.01 level of significance, what conclusion should the builder draw regarding the inclusion of School in the regression model?


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