at is the exact effect (in percent) of an increase of 10 years of education on predicted wage? at is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag hours per week? Source SS df MS Number of obs 935 F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared %3D 0.1367 0.1330 %3D Total 165.656283 934 .177362188 Root MSE .39214 lwage Coef. Std. Err. P>|t| [95% Conf. Interval] educ .0400982 .0068351 5.87 0.000 .0266843 .0535122 IQ .005914 .0009967 5.93 0.000 .0039579 .0078701 hours .0035899 .013037 0.28 0.783 -.0219954 .0291752 hours2 -.0000842 .0001298 -0.65 0.517 -.0003389 .0001706 _cons 5.649044 .3240363 17.43 0.000 5.013117 6.284971 where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
at is the exact effect (in percent) of an increase of 10 years of education on predicted wage? at is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag hours per week? Source SS df MS Number of obs 935 F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared %3D 0.1367 0.1330 %3D Total 165.656283 934 .177362188 Root MSE .39214 lwage Coef. Std. Err. P>|t| [95% Conf. Interval] educ .0400982 .0068351 5.87 0.000 .0266843 .0535122 IQ .005914 .0009967 5.93 0.000 .0039579 .0078701 hours .0035899 .013037 0.28 0.783 -.0219954 .0291752 hours2 -.0000842 .0001298 -0.65 0.517 -.0003389 .0001706 _cons 5.649044 .3240363 17.43 0.000 5.013117 6.284971 where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag
40 hours per week?
Source
df
MS
Number of obs
935
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
0.1367
0.1330
Total
165.656283
934
.177362188
Root MSE
.39214
lwage
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ
.0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
_cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F56a1c4f6-f25c-4730-9a3e-6958f52f6cc7%2F80a30e80-3c8b-4ba2-89b8-ac6e7af4dc8c%2Fh7vug2_processed.png&w=3840&q=75)
Transcribed Image Text:What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag
40 hours per week?
Source
df
MS
Number of obs
935
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
0.1367
0.1330
Total
165.656283
934
.177362188
Root MSE
.39214
lwage
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ
.0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
_cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.
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