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 |
0.7345 |
R Square |
0.5395 |
Adjusted R Square |
0.5195 |
Standard Error |
2134.9715 |
Observations |
49 |
ANOVA |
|||||
df |
SS |
MS |
F |
Significance F |
|
Regression |
2 |
245,644,973.9500 |
122,822,486.9750 |
26.9460 |
1.8E-08 |
Residual |
46 |
209,672,760.0092 |
4,558,103.4785 |
||
Total |
48 |
455,317,733.9592 |
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
|
Intercept |
14271.51879 |
2,525.5672 |
5.6508 |
0.000000963 |
9187.8157 |
19,355.2219 |
Education (Years) |
2351.3035 |
337.7109 |
6.9625 |
0.00000001 |
1671.5267 |
3031.0803 |
Experience (Years) |
832.8612 |
392.0947 |
2.1241 |
0.039069201 |
43.6155 |
1622.1069 |
Step 1 of 2:
What would be your expected salary with no education and no experience?
Step 2 of 2:
How much would you expect your salary to increase if you had one more year of education?
the regression equation from the given table is
ans 1 )
expected salary with no education and no experience will be
expected salary = 14271.519
ans 2 )
Expect your salary to increase if you had one more year of education is
Expect salary to increase if you had one more year of education is 16622.819
Get Answers For Free
Most questions answered within 1 hours.