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Instruction 13-15
a Financial Analyst Wanted to Examine the Relationship

question 226

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Instruction 13-15
A financial analyst wanted to examine the relationship between salary (in $1,000)and 4 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:
SUMMARY
Regression Statistics
 Multiple R 0.992 R Square 0.984 Adj. R Square 0.979 Std. Error 2.26743 Observations 20\begin{array} { l l } \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}
ANOVA
df SS  MS F Signif F Regression 44609.831641152.45791224.1600.0001 Residual 1577.118365.14122 Total 194686.95000\begin{array} { l l l l l l } & \boldsymbol { d f } & \text { SS } & \text { MS } & \boldsymbol { F } & \text { Signif } \boldsymbol { 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}
 Coeff  StdError t Stat P-Value  Intercept 9.6111982.779886383.4570.0035 Age 1.3276950.1149193011.5530.0001 Exper 0.1067050.142655590.7480.4660 Degrees 7.3113320.803241879.1020.0001 Prevjobs 0.5041680.447715731.1260.2778\begin{array} { l l l l l } & \text { Coeff } & \text { StdError } & \boldsymbol { t } \text { Stat } & \boldsymbol { 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 13-15,the net regression coefficient of X2 is ________.


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