Vnat is the exact effect (in percent) of an increase of 10 years of education on predicted wage? Vhat is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag -0 hours per week? Source df MS Number of obs 935 %3D F (4, 930) 36.82 %3D Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared 0.1367 0.1330 %3D 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 lwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
Vnat is the exact effect (in percent) of an increase of 10 years of education on predicted wage? Vhat is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag -0 hours per week? Source df MS Number of obs 935 %3D F (4, 930) 36.82 %3D Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared 0.1367 0.1330 %3D 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 lwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Related questions
Question
![What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag
40 hours per week?
Source
SS
df
MS
Number of obs
935
%3D
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
Сoef.
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$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.
I| |||| | |||](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F56a1c4f6-f25c-4730-9a3e-6958f52f6cc7%2F09d64e10-4d0e-45b9-b12e-00829ca4828a%2Febkttjn_processed.png&w=3840&q=75)
Transcribed Image Text:What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on averag
40 hours per week?
Source
SS
df
MS
Number of obs
935
%3D
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
Сoef.
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.
I| |||| | |||
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