Consider the following regression estimates (FN6) Source SS df MS Number of obs = 526 64.11 F(3, 522) = Model 1927.87673 3 642.625576 Prob > F = 0.0000 Residual 5232.53756 522 10.0240183 R-squared 0.2692 Adj R-squared = 0.2650 Total 7160.41429 525 13.6388844 Root MSE = 3.1661 wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .5953429 .0530251 11.23 .4911741 .6995118 0.000 7.27 0.000 exper .268287 .0368969 .1958023 .3407717 exper2 -.0046123 .000822 -5.61 0.000 -.006227 -.0029975 _cons -3.96489 .7521526 -5.27 0.000 -5.442508 -2.487272 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper). At how many years is the marginal effect of increasing experience on predicted wage equal to zero? Only state the number in your answer (e.g. don't write US$ or $ or years).
Consider the following regression estimates (FN6) Source SS df MS Number of obs = 526 64.11 F(3, 522) = Model 1927.87673 3 642.625576 Prob > F = 0.0000 Residual 5232.53756 522 10.0240183 R-squared 0.2692 Adj R-squared = 0.2650 Total 7160.41429 525 13.6388844 Root MSE = 3.1661 wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .5953429 .0530251 11.23 .4911741 .6995118 0.000 7.27 0.000 exper .268287 .0368969 .1958023 .3407717 exper2 -.0046123 .000822 -5.61 0.000 -.006227 -.0029975 _cons -3.96489 .7521526 -5.27 0.000 -5.442508 -2.487272 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper). At how many years is the marginal effect of increasing experience on predicted wage equal to zero? Only state the number in your answer (e.g. don't write US$ or $ or years).
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section: Chapter Questions
Problem 6SGR
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