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 0.73720.7372 R Square 0.54340.5434 Adjusted R Square 0.52350.5235 Standard Error 2120.66062120.6606 Observations 4949     ANOVA   dfdf SSSS MSMS F� Significance F� Regression 22 246,191,336.3605246,191,336.3605 123,095,668.1803123,095,668.1803 27.371627.3716 1.5E-081.5E-08 Residual 4646 206,871,255.7619206,871,255.7619 4,497,201.21224,497,201.2122     Total 4848 453,062,592.1224453,062,592.1224             Coefficients Standard Error t� Stat P-value Lower 95%95% Upper 95%95% Intercept 14262.1701214262.17012 2,508.63812,508.6381 5.68525.6852 0.0000008560.000000856 9212.54359212.5435 19,311.796719,311.7967 Education (Years) 2354.97312354.9731 335.4472335.4472 7.02047.0204 0.0000000080.000000008 1679.75291679.7529 3030.19333030.1933 Experience (Years) 830.0759830.0759 389.4664389.4664 2.13132.1313 0.0384398390.038439839 46.120746.1207 1614.03111614.0311     Step 1 of 2 :   What would be your expected salary with no education and no experience?

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