SCENARIO 17-3 a Financial Analyst Wanted to Examine the Relationship $\$ 1,000$

SCENARIO 17-3 A financial analyst wanted to examine the relationship between salary (in $\$ 1,000$ ) and 4 variables: age $\left( X _ { 1 } = \mathrm { Age } \right)$ , experience in the field $\left( X _ { 2 } = \right.$ Exper $)$ , number of degrees $\left( X _ { 3 } = \right.$ Degrees $)$ , and number of previous jobs in the field ( $X _ { 4 } =$ Prevjobs). He took a sample of 20 employees and obtained the following Microsoft Excel output:

SUMMARY OUTPUT

$\begin{array}{ll}{\text { Regression Statistics }} \\\text { Multiple R } & 0.992 \\\text { R Square } & 0.984 \\\text { Adjusted R Square } & 0.979 \\\text { Standard Error } & 2.26743 \\\text { Observations } & 20\end{array}$


$\begin{array}{lrrrrr} & d f &{\text { SS }} & \text { MS } & F & \text { Signif } F \\\text { Regression } & 4 & 4609.83164 & 1152.45791 & 224.160 & 0.0001 \\\text { Residual } & 15 & 77.11836 & 5.14122 & & \\\text { Total } & 19 & 4686.95000 & & &\end{array}$

$\begin{array}{lrrrr} & {\text { Coeff }} & \text { StdError } & {\text { Stat }} & \text { P-value } \\\text { Intercept } & -9.611198 & 2.77988638 & -3.457 & 0.0035 \\\text { Age } & 1.327695 & 0.11491930 & 11.553 & 0.0001 \\\text { Exper } & -0.106705 & 0.14265559 & -0.748 & 0.4660 \\\text { Degrees } & 7.311332 & 0.80324187 & 9.102 & 0.0001 \\\text { Prevjobs } & -0.504168 & 0.44771573 & -1.126 & 0.2778\end{array}$
-Referring to Scenario 17-3, the value of the coefficient of multiple determination, $r ^ { 2 } Y .1234$ , is
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