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 0.7339 R Square 0.5386 Adjusted R Square 0.5185 Standard Error 2137.5200 Observations 49 ANOVA SS df Regression 2 245,370,679.3850 122,685,339.6925 26.8517 MS F Significance F 1.9E-08 Total Residual 46 210,173,612.6150 48 455,544,292.0000 4,568,991.5786 Coefficients Standard Error Intercept Education (Years) 14290.37278 2350.8671 2,528.5819 338.1140 Experience (Years) 829.3167 392.5627 t Stat P-value 5.6515 0.000000961 9200.6014 6.9529 0.000000011 2.1126 0.040093183 Lower 95 % Upper 95% 19,380.1442 1670.2789 3031.4553 39.129 1619.5044 Step 2 of 2: How much would you expect your salary to increase if you had one more year of education?

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter7: Production Economics
Section: Chapter Questions
Problem 1.3CE
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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
0.7339
R Square
0.5386
Adjusted R Square
0.5185
Standard Error
2137.5200
Observations
49
ANOVA
SS
df
Regression 2 245,370,679.3850 122,685,339.6925 26.8517
MS
F
Significance F
1.9E-08
Total
Residual 46 210,173,612.6150
48 455,544,292.0000
4,568,991.5786
Coefficients Standard Error
Intercept
Education (Years)
14290.37278
2350.8671
2,528.5819
338.1140
Experience (Years)
829.3167
392.5627
t Stat P-value
5.6515 0.000000961 9200.6014
6.9529 0.000000011
2.1126 0.040093183
Lower 95 %
Upper 95%
19,380.1442
1670.2789
3031.4553
39.129
1619.5044
Step 2 of 2: How much would you expect your salary to increase if you had one more year of education?
Transcribed Image Text: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 0.7339 R Square 0.5386 Adjusted R Square 0.5185 Standard Error 2137.5200 Observations 49 ANOVA SS df Regression 2 245,370,679.3850 122,685,339.6925 26.8517 MS F Significance F 1.9E-08 Total Residual 46 210,173,612.6150 48 455,544,292.0000 4,568,991.5786 Coefficients Standard Error Intercept Education (Years) 14290.37278 2350.8671 2,528.5819 338.1140 Experience (Years) 829.3167 392.5627 t Stat P-value 5.6515 0.000000961 9200.6014 6.9529 0.000000011 2.1126 0.040093183 Lower 95 % Upper 95% 19,380.1442 1670.2789 3031.4553 39.129 1619.5044 Step 2 of 2: How much would you expect your salary to increase if you had one more year of education?
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