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 0.7352 R Square 0.5405 Adjusted R Square 0.5205 Standard Error 2131.1820 Observations 49 ANOVA df SS Regression 2 245,793,126.4218 MS 122,896,563.2109 27.0582 F Significance F 1.7E-08 Residual 46 208,929,085.5374 Total 48 454,722,211.9592 4,541,936.6421 Coefficients Standard Error t Stat P-value Lower 95 % Upper 95 % Intercept 14268.68236 2,521.0844 Education (Years) 2352.2698 337.1115 Experience (Years) 832.2096 391.3987 5.6597 0.000000934 6.9777 0.00000001 2.1262 0.03888471 9194.0027 19,343.3621 1673.6995 3030.8401 44.3649 1620.0543 Step 1 of 2: What would be your expected salary with no education and no experience?
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 0.7352 R Square 0.5405 Adjusted R Square 0.5205 Standard Error 2131.1820 Observations 49 ANOVA df SS Regression 2 245,793,126.4218 MS 122,896,563.2109 27.0582 F Significance F 1.7E-08 Residual 46 208,929,085.5374 Total 48 454,722,211.9592 4,541,936.6421 Coefficients Standard Error t Stat P-value Lower 95 % Upper 95 % Intercept 14268.68236 2,521.0844 Education (Years) 2352.2698 337.1115 Experience (Years) 832.2096 391.3987 5.6597 0.000000934 6.9777 0.00000001 2.1262 0.03888471 9194.0027 19,343.3621 1673.6995 3030.8401 44.3649 1620.0543 Step 1 of 2: What would be your expected salary with no education and no experience?
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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