Exhibit 14-2The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years) and X3 family size (number of family members in household). The multiple regression output is shown below:

\begin{array}{l}\text { Summary measures }\\\begin{array}{ll}\hline \text { Multiple R } & 0.8440 \\\text { R-Square } & 0.7123 \\\text { Adi R-Square } & 0.6644 \\\text { StErr of } & 0.5598 \\\text { Estimate } & \\\hline\end{array}\end{array}

\begin{array}{l}\text { ANOVA Table }\\\begin{array}{l|lllll}\hline \text { Source } & d f & S S & M S & F & p \text {-value } \\\hline \text { Explained } & 3 & 13.9682 & 4.6561 & 14.8564 & 0.0000 \\\text { Unexplained } & 18 & 5.6413 & 0.3134 & & \\\hline\end{array}\end{array}

\begin{array}{l}\underline{\text { Regression coefficients }}\\\begin{array}{l|llll|}\hline & \text { Coefficient } & \text { StdErr } & \text { t-value } & p \text {-value } \\\hline \text { Constant } & 1.683 & 1.1696 & 1.4389 & 0.1674 \\\text { Age } & -0.0498 & 0.0199 & -2.5018 & 0.0222 \\\text { Education } & 0.2135 & 0.0503 & 4.2426 & 0.0005 \\\text { Family Size } & 0.0405 & 0.0784 & 0.5168 & 0.6116 \\\hline\end{array}\end{array}

-Refer to Exhibit 14-2. Interpret each of the estimated regression coefficients of the regression model above.

Exhibit 14-3 the Quarterly Numbers of Applications for Home Mortgage Loans at Loans

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