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SCENARIO 13-8
a Financial Analyst Wanted to Examine the Relationship

question 105

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SCENARIO 13-8
A financial analyst wanted to examine the relationship between salary (in $1,000) and 2 variables: age (X1 = Age) and experience in the field (X2 = Exper).He took a sample of 20 employees and obtained the following Microsoft Excel output:  Regression Statistics  Multiple R 0.8535 R Square 0.7284 Adjusted R Square 0.6964 Standard Error 10.5630 Observations 20 ANOYA df SS  MS  F  Siqnificonce F  Regression 25086.57642543.288222.79410.0000 Residual 171896.8050111.5768 Total 196983.3814 Coefficients  Standard Error t Stat  P-value  Lower 95%  Upper 95%  Intercept 1.57409.27230.16980.867217.988821.1368 Age 1.30450.19566.66780.00000.89171.7173 Exper 0.14780.19440.76040.45740.55800.2624\begin{array}{l}\begin{array} { l r } \hline { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.8535 \\\text { R Square } & 0.7284 \\\text { Adjusted R Square } & 0.6964 \\\text { Standard Error } & 10.5630 \\\text { Observations } & 20 \\\hline\end{array}\\\\\text { ANOYA }\\\begin{array} { l r c c c c } & d f & \text { SS } & \text { MS } & \text { F } & \text { Siqnificonce F } \\\hline \text { Regression } & 2 & 5086.5764 & 2543.2882 & 22.7941 & 0.0000 \\\text { Residual } & 17 & 1896.8050 & 111.5768 & & \\\text { Total } & 19 & 6983.3814 & & & \\\hline\end{array}\\\\\begin{array} { l r r r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & 1.5740 & 9.2723 & 0.1698 & 0.8672 & - 17.9888 & 21.1368 \\\text { Age } & 1.3045 & 0.1956 & 6.6678 & 0.0000 & 0.8917 & 1.7173 \\\text { Exper } & - 0.1478 & 0.1944 & - 0.7604 & 0.4574 & - 0.5580 & 0.2624 \\\hline\end{array}\end{array}
-Referring to SCENARIO 13-8, _% of the variation in salary can be explained by the variation in age while holding experience constant.


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