Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience.   Regression Statistics Multiple R 0.73520.7352 R Square 0.54050.5405 Adjusted R Square 0.52050.5205 Standard Error 2131.18202131.1820 Observations 4949     ANOVA   dfdf SSSS MSMS F� Significance F� Regression 22 245,793,126.4218245,793,126.4218 122,896,563.2109122,896,563.2109 27.058227.0582 1.7E-081.7E-08 Residual 4646 208,929,085.5374208,929,085.5374 4,541,936.64214,541,936.6421     Total 4848 454,722,211.9592454,722,211.9592             Coefficients Standard Error t� Stat P-value Lower 95%95% Upper 95%95% Intercept 14268.6823614268.68236 2,521.08442,521.0844 5.65975.6597 0.0000009340.000000934 9194.00279194.0027 19,343.362119,343.3621 Education (Years) 2352.26982352.2698 337.1115337.1115 6.97776.9777 0.000000010.00000001 1673.69951673.6995 3030.84013030.8401 Experience (Years) 832.2096832.2096 391.3987391.3987 2.12622.1262 0.038884710.03888471 44.364944.3649 1620.05431620.0543     Step 2 of 2 :   How much would you expect your salary to increase if you stayed at the company for another year?

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