Consider estimating the relationship between annual income (income) and a dummy variable equal to 1 if if an individual is a female and 0 otherwise gender by running an OLS regression in Stata. The results are in Figure 1. . reg income gender, robust Linear regression Number of obs 4,779 %3D F(1, 4777) 188.63 Prob > F 0.0000 R-squared 0.0394 Root MSE 36681 Robust income Coefficient std. err. t P>|t| [95% conf. interval] gender 1082.551 -13.73 0.000 -16990.16 -12745.57 _cons 2033.434 21.18 0.000 39072.15 47045.09 The OLS estimate of the coefficient of gender is: a. -78.8456 b. 14,863.42523 c. -14,863.42523 O d. The information given in the question is not sufficient to provide an answer
Consider estimating the relationship between annual income (income) and a dummy variable equal to 1 if if an individual is a female and 0 otherwise gender by running an OLS regression in Stata. The results are in Figure 1. . reg income gender, robust Linear regression Number of obs 4,779 %3D F(1, 4777) 188.63 Prob > F 0.0000 R-squared 0.0394 Root MSE 36681 Robust income Coefficient std. err. t P>|t| [95% conf. interval] gender 1082.551 -13.73 0.000 -16990.16 -12745.57 _cons 2033.434 21.18 0.000 39072.15 47045.09 The OLS estimate of the coefficient of gender is: a. -78.8456 b. 14,863.42523 c. -14,863.42523 O d. The information given in the question is not sufficient to provide an answer
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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![Consider estimating the relationship between annual income (income) and a dummy variable equal to 1 if if an individual is a female and 0
otherwise gender by running an OLS regression in Stata. The results are in Figure 1.
reg income gender, robust
Linear regression
Number of obs
4,779
F(1, 4777)
188.63
Prob > F
0.0000
R-squared
0.0394
Root MSE
36681
Robust
income
Coefficient std. err.
t
P>|t|
[95% conf. interval]
gender
1082.551
-13.73
0.000
-16990.16
-12745.57
_cons
2033.434
21.18
0.000
39072.15
47045.09
The OLS estimate of the coefficient of gender is:
O a. -78.8456
O b. 14,863.42523
O c.
-14,863.42523
O d. The information given in the question is not sufficient to provide an answer
II || || II||](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9a398711-6bb1-446b-9b69-373cfacdd600%2Fdb9c7eed-0386-4ff2-974e-b5c3dd7e6bcc%2Fjedzrx9_processed.png&w=3840&q=75)
Transcribed Image Text:Consider estimating the relationship between annual income (income) and a dummy variable equal to 1 if if an individual is a female and 0
otherwise gender by running an OLS regression in Stata. The results are in Figure 1.
reg income gender, robust
Linear regression
Number of obs
4,779
F(1, 4777)
188.63
Prob > F
0.0000
R-squared
0.0394
Root MSE
36681
Robust
income
Coefficient std. err.
t
P>|t|
[95% conf. interval]
gender
1082.551
-13.73
0.000
-16990.16
-12745.57
_cons
2033.434
21.18
0.000
39072.15
47045.09
The OLS estimate of the coefficient of gender is:
O a. -78.8456
O b. 14,863.42523
O c.
-14,863.42523
O d. The information given in the question is not sufficient to provide an answer
II || || II||
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