2. Following Question 1. The researcher thought that another variable, gender, might also affect the income level. Thus, he created a dummy variable for gender (1 for male and 0 for female) and estimated the regression model with two independent variables. SUMMARY OUTPUT Regression Statistics Multiple R 0.959 R Square 0.920 Adjusted R Square Standard Error 0.898 3.988 Observations 10.000 ANOVA df SS MS F Significance F Regression 2.000 1,286.766 643.383 40.451 0.000 Residual 7.000 111.337 15.905 Total 9.000 1,398.103 Lower 95% Upper 95% Lower 95.0% Upper 95.0% (9.301) Coefficients tandard Erroi t Stat P-value 10.140 8.222 1.233 0.257 29.581 (9.301) 29.581 Intercept Years in College 11.700 3.454 3.388 0.012 3.533 19.867 3.533 19.867 Gender 1.950 6.306 0.309 0.766 (12.961) 16.861 (12.961) 16.861
2. Following Question 1. The researcher thought that another variable, gender, might also affect the income level. Thus, he created a dummy variable for gender (1 for male and 0 for female) and estimated the regression model with two independent variables. SUMMARY OUTPUT Regression Statistics Multiple R 0.959 R Square 0.920 Adjusted R Square Standard Error 0.898 3.988 Observations 10.000 ANOVA df SS MS F Significance F Regression 2.000 1,286.766 643.383 40.451 0.000 Residual 7.000 111.337 15.905 Total 9.000 1,398.103 Lower 95% Upper 95% Lower 95.0% Upper 95.0% (9.301) Coefficients tandard Erroi t Stat P-value 10.140 8.222 1.233 0.257 29.581 (9.301) 29.581 Intercept Years in College 11.700 3.454 3.388 0.012 3.533 19.867 3.533 19.867 Gender 1.950 6.306 0.309 0.766 (12.961) 16.861 (12.961) 16.861
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.3: Measures Of Spread
Problem 1GP
Related questions
Question
wrie down the estimated regression equation?
Transcribed Image Text:2. Following Question 1. The researcher thought that another variable, gender, might also affect the income level. Thus, he created a dummy variable for gender (1 for male and 0 for female) and estimated the
regression model with two independent variables,
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
0.959
0.920
Adjusted R Square
0.898
Standard Error
3.988
Observations
10.000
ANOVA
df
SS
MS
F
Significance F
Regression
2.000
1,286.766
643.383
40.451
0.000
Residual
7.000
111.337
15.905
Total
9.000
1,398.103
Lower 95% Upper 95% Lower 95.0% Upper 95.0%
(9.301)
Coefficients itandard Erro
t Stat
P-value
10.140.
8.222
1.233
0.257
29.581
(9.301)
29.581
Intercept
Years in College
11.700
3.454
3.388
0.012
3.533
19.867
3.533
19.867
1.950
6.306
0.309
0.766
(12.961)
16.861
(12.961)
16.861
Gender
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