logWage=B1+ B₂ educ + €, where . 1. logWage means the log of yearly wage measured in dollars. 2. educ means years of education (schooling) The regression output is given below: . reg logwage educ Source | SS df MS Number of obs = 100 F(2, 97) = 97.20 Model 0.250000 1 .246632 Prob > F = 0.0000 Residual | 0.250000 98 .002537 R-squared = 0.5000 Adj R-squared = 0.4900 Total | 20000.00 99 200.00 Root MSE = 0.0503 logwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] educ | 0.40000 0.200000 2.00 0.050 0.0000000 0.800000 _cons | 5.00000 0.100000 10.00 0.000 4.8000000 5.200000

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Question

Answer the following questions based on the regression output:

What is the expected value of the Log of Wage for a person with 10 years of education?

(a) 9

(b) 15

(c) 5

(d) 13

(e) 25

logWage=B1+ B₂ educ + €, where
.
1. logWage means the log of yearly wage measured in dollars.
2. educ means years of education (schooling)
The regression output is given below:
.
reg logwage educ
Source |
SS
df
MS
Number of obs
=
100
F(2, 97)
=
97.20
Model
0.250000
1
.246632
Prob > F
=
0.0000
Residual | 0.250000
98
.002537
R-squared
=
0.5000
Adj R-squared
=
0.4900
Total | 20000.00
99
200.00
Root MSE
=
0.0503
logwage |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ | 0.40000
0.200000
2.00 0.050
0.0000000
0.800000
_cons |
5.00000
0.100000
10.00 0.000
4.8000000
5.200000
Transcribed Image Text:logWage=B1+ B₂ educ + €, where . 1. logWage means the log of yearly wage measured in dollars. 2. educ means years of education (schooling) The regression output is given below: . reg logwage educ Source | SS df MS Number of obs = 100 F(2, 97) = 97.20 Model 0.250000 1 .246632 Prob > F = 0.0000 Residual | 0.250000 98 .002537 R-squared = 0.5000 Adj R-squared = 0.4900 Total | 20000.00 99 200.00 Root MSE = 0.0503 logwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] educ | 0.40000 0.200000 2.00 0.050 0.0000000 0.800000 _cons | 5.00000 0.100000 10.00 0.000 4.8000000 5.200000
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