SUMMARY OUTPUT $\text { Figure } 4.1$ -Suppose You Are Given the Excel Output in Figure You

SUMMARY OUTPUT
$\begin{array}{lc}\hline \text { Regression Statistics } & \\\hline \text { Multiple R } & 0.216543528 \\\text { R square } & 0.046891099 \\\text { Adjusted R Square } & 0.042101608 \\\text { Standard Error } & 1155621.367 \\\text { Observations } & 201 \\\hline\end{array}$

$\begin{array}{l}\text { ANOVA }\\\begin{array}{lccccc}\hline & \text { of } & S S & \text { MS } & \text { F } & \text { Significance } F \\\hline \text { Regression } & 1 & 1.30747 E+13 & 1.30747 E+13 & 9.790411975 & 0.00201776 \\\text { Residual } & 199 & 2.65757 E+14 & 1.33546 E+12 & \\\text { Total } & 200 & 2.78831 E+14 & & \\\hline\end{array}\end{array}$

$\begin{array}{lcccccc}\hline & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -7,773,135.558 & 2,867,254.773 & -2.711002745 & 0.007294364 & -13,427,237,240 & -2,119,033.877 \\\text { Yards Per Drive } & 30,737.523 & 9,823.548 & 3.128963403 & 0.00201776 & 11,365.913 & 50,109.132 \\\hline\end{array}$

$\text { Figure } 4.1$
-Suppose you are given the Excel output in Figure You would conclude that each additional Yard Per Drive is estimated to be associated with

A) a $7,773,135.558 decrease in annual earnings.
B) a $2,867,254.773 increase in annual earnings.
C) a $30,737.523 increase in annual earnings.
D) a $9,823.548 increase in annual earnings.