earn98 = 4.84 + 2.429train+0.372earn96+0.365educ – 1.84 age + 2.446 married(1.06)(0.44)(0.011)(0.063)(0.016)(0.49)whereearn98 = 1998 earnings, in thousands of dollarstrain =1 if the individual participated in the training program, and =0 otherwiseearn96 = 1996 earnings, in thousands of dollarseduc = years of educationage = age, in yearsmarried =1 if the individual is married, and =0 otherwiseSuppose that there is a high degree of correlation (but not perfect) between education, age, and marital status.True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the trainingprogram on 1998 earnings, T.TrueFalse

Name: earn98 = 4.84 + 2.429train+0.372earn96+0.365educ – 1.84 age + 2.446 m
Uploaded: 2024-03-20T07:07:12.000Z
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Description: earn98 = 4.84 + 2.429train+0.372earn96+0.365educ – 1.84 age + 2.446 married(1.06)(0.44)(0.011)(0.063)(0.016)(0.49)whereearn98 = 1998 earnings, in thousands of dollarstrain =1 if the individual participated in the training program, and =0 otherwiseea

In regression analysis, the problem of multicollinearity arises when one independent variable is…

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Suppose that there is a high degree of correlation (but not perfect) between education, age, and marital status. True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the training program on 1998 earnings, T.