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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.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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
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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$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
Transcribed Image Text:What is the exact effect (in percent) of an increase of 10 years of education on predicted wage? What is the predicted monthly wage in US$ 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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