The following results are from data where the dependent variable is SALARY, the independent variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0 for males. a) Complete the results

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5) The following results are from data where the dependent variable is SALARY, the independent variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0 for males. a) Complete the results
5) The following results are from data where the dependent variable is SALARY, the independent
variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0
for males.
a) Complete the results (20)
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
827
ANOVA
df
SS
MS
F
Significance F
Regression
75305189884
3.20592E-36
Residual
332444000000
Total
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
-26599.5
5077.2
-5.24
2.052E-07
-36565.2
-16633.8
AGE
520.2
86.3
6.03
2.469E-09
350.9
689.5
EDUCATION
2493.8
216.1
11.54
1.135E-28
FEMALE
-4669.2
1526.6
0.0022962
-7665.7
-1672,7
Based on the regression results:
a) What is the estimated regression equation?
Transcribed Image Text:5) The following results are from data where the dependent variable is SALARY, the independent variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0 for males. a) Complete the results (20) SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 827 ANOVA df SS MS F Significance F Regression 75305189884 3.20592E-36 Residual 332444000000 Total Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -26599.5 5077.2 -5.24 2.052E-07 -36565.2 -16633.8 AGE 520.2 86.3 6.03 2.469E-09 350.9 689.5 EDUCATION 2493.8 216.1 11.54 1.135E-28 FEMALE -4669.2 1526.6 0.0022962 -7665.7 -1672,7 Based on the regression results: a) What is the estimated regression equation?
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