Consider the following Stata regression output (IDMC5) Source SS df MS Number of obs 935 %3D F(1, 933) 111.79 %3D Model 16340644.5 1 16340644.5 Prob > F %3D 0.0000 Residual R-squared Adj R-squared 136375524 933 146168.836 0.1070 %3D %3D 0.1060 Total 152716168 934 163507.675 Root MSE 382.32 %3D wage Coefficient Std. err. t P>|t| [95% conf. interval] educ 60.21428 5.694982 10.57 0.000 49.03783 71.39074 cons 146.9524 77.71496 1.89 0.059 -5.56393 299.4688 where wage is monthly wage in US$ and educ is years of education. What is the predicted effect of a 5 year increase of education on wage?
Consider the following Stata regression output (IDMC5) Source SS df MS Number of obs 935 %3D F(1, 933) 111.79 %3D Model 16340644.5 1 16340644.5 Prob > F %3D 0.0000 Residual R-squared Adj R-squared 136375524 933 146168.836 0.1070 %3D %3D 0.1060 Total 152716168 934 163507.675 Root MSE 382.32 %3D wage Coefficient Std. err. t P>|t| [95% conf. interval] educ 60.21428 5.694982 10.57 0.000 49.03783 71.39074 cons 146.9524 77.71496 1.89 0.059 -5.56393 299.4688 where wage is monthly wage in US$ and educ is years of education. What is the predicted effect of a 5 year increase of education on wage?
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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