Please solve #4

4. In the equation 1 above, add a squared term of experience as independent variable. Is the relationship between log of wage and experience non-linear? State the hypothesis clearly and test the significance at a = 5%. (2 points) SUMMARY OUTPUT For exper Ho: B2 = 0 The relationship between log of wage and Regression Statistics Multiple R 0.3989047 Ha: B2 /= 0 experience is non-linear. We would expect this to be R Square 0.1591249 true because your wage would not be affected as Adjusted R: 0.1540132 Standard Er 0.3791373 For exper^2 much from experience you gain later in your career Observation 663 Ho: B3 = 0 compared to the effect on wage from experience Ha: B3 /= 0 you gained when you were beginning your career. ANOVA df SS MS F ignificance F = Regression 4 17.898876 4.4747191 31.129537 9.2E-24 Exper: 14.41| > |1.96| > Reject Ho Residual 658 94.584289 0.1437451 Total 662 112.48317 Exper is Statistically Significant at a = 5%. Coefficients tandard Erre t Stat P-value Lower 95% Up Intercept 5.5430834 0.1419558 39.047961 1.72E-173 5.2643425 5. educ 0.0763886 0.0075169 10.162275 1.236E-22 0.0616286 0. exper 0.0079634 0.0154608 0.5150742 0.6066742 -0.022395 0.( Exper^2: |0.67 | Do not Reject Ho exper^2 0.0004488 0.0006674 0.6725214 0.5014879 -0.000862 0. tenure 0.0095632 0.0030992 3.0856614 0.0021162 0.0034776 0.610480