Instruction 13 $\text { OUTPUT }$ Note: Adj R Square = Adjusted R Square; Std

Instruction 13.13
A financial analyst wanted to examine the relationship between salary (in $1,000) and four variables: age (X₁ = Age), experience in the field (X₂ = Exper), number of degrees (X₃ = Degrees) and number of previous jobs in the field (X₄ = Prevjobs). He took a sample of 20 employees and obtained the following Microsoft Excel output:
$\text { OUTPUT }$
$\begin{array}{ll}\text { SUMMARY}\\\text { Regression }&\text { Statistics}\\\text { Multiple R } & 0.992 \\\text { R Square } & 0.984 \\\text { Adj. R Square } & 0.979 \\\text { Std. Error } & 2.26743 \\\text { Observations } & 20\end{array}$

$\begin{array}{l}\text { ANOVA }\\\begin{array}{llllll} & \text { df } & \text { SS } & \text { MS } & F & \text { Signif F } \\\text { Regression } & 4 & 4609.83164 & 1152.45791 & 224.160 & 0.0001 \\\text { Residual } & 15 & 77.11836 & 5.14122 & & \\\text { Total } & 19 & 4686.95000 & & &\end{array}\end{array}$

$\begin{array}{lllll} & \text { Coeff } & \text { Std Error } & t \text { Stat } & p \text { value } \\\text { Intercept } & -9.611198 & 2.77988638 & -3.457 & 0.0035 \\\text { Age } & 1.327695 & 0.11491930 & 11.553 & 0.0001 \\\text { Exper } & -0.106705 & 0.14265559 & -0.748 & 0.4660 \\\text { Degrees } & 7.311332 & 0.80324187 & 9.102 & 0.0001 \\\text { Prevjobs } & -0.504168 & 0.44771573 & -1.126 & 0.2778\end{array}$

Note: Adj. R Square = Adjusted R Square; Std. Error = Standard Error
-Referring to Instruction 13.13,the net regression coefficient of X₂ is ___________.