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. b) How much of the variation in income is explained by the regressors? c) What is the standard error of the error term in the regression equation? d) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?
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. b) How much of the variation in income is explained by the regressors? c) What is the standard error of the error term in the regression equation? d) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
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.
b) How much of the variation in income is explained by the regressors?
c) What is the standard error of the error term in the regression equation?
d) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?
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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