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problem set 3

# problem set 3 - #1(a BMI = 28.44 0.882 0 = 28.44 For...

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#1) (a) · 28.44 0.882 0 28.44 BMI = - × = For individuals in urban areas we have Urban = 1, so then · 28.44 0.882 1 27.558 BMI = - × = (b) The slope coefficient 1 ˆ 0.882 β = - is the point estimate of the difference. The standard error is s e = 0.185. The approximate confidence interval is CI = (-0.882 – 1.96*0.185, -0.882 + 1.96*0.185) = (-1.2446, -0.5194) (c) If I suspect that the variance of people’s BMI in urban locations is not the same as the variance of people’s BMI in rural locations, then I suspect that there is a heteroskedasticity problem, which means that the variance of the error term is not constant across all the values of the independent variable(s). This would be a violation of the regression assumption that ( 29 2 0, i N ε σ : , where 2 σ is constant, and it doesn’t change across levels of the independent variable(s).

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#2) 6.2 (a) Yes, workers with college degrees earn \$5.46/hour more, on average, than those without a college degree. 6.2 (b) Yes, males earn \$2.64/hour more, on average, than females. 6.3 (a) The table doesn’t indicate whether or not age is a significant predictor.
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