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Unformatted text preview: NAME: Econ 334: Practice Final Exam 1. Of the four assumptions for simple linear regression, which is most directly connected with estimating the slope coeﬃcient? 2. Suppose you run a regression of student’s final exam scores on their previous previous grades: final i = β + β 1 midterm 1 i + β 2 midterm 2 i + u i (a) How many points more would we expect you to do on the final if you had scored 5 more points on midterm2? (b) Now suppose that students with lower midterm grades studied harder for the final. What does this do to our prediction of your final grade? Is it too high or too low? Be specific about what is correlated with what. 3. You run a complex model to determine if cigarette prices ( cigprice ) determine number of cigarettes smoked per day ( cigs ). white is a dummy variable which is one if the person is white. Call: lm(formula = cigs ~ logIncome + age + ageSq + cigprice + educ + white + white * educ, data = smoke) Residuals: Min 1Q Median 3Q Max15.0389.1496.704 8.093 71.017 Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 0.647517 10.8391550.060 0.952 logIncome 0.676953 0.761178 0.889 0.374 age 0.734925 0.167618 4.385 1.33e05 *** ageSq0.008627 0.0018164.751 2.43e06 *** cigprice0.035384 0.1069310.331 0.741 educ0.650954 0.4434221.468 0.143 white2.432749 6.0944920.399 0.690 educ:white 0.183638 0.473142 0.388 0.698 Residual standard error: 13.56 on 748 degrees of freedom Multiple RSquared: 0.04161,Adjusted Rsquared: 0.03264 Fstatistic: 4.639 on 7 and 748 DF, pvalue: 4.246e05 1 (a) How many more or less cigarettes does a person smoke if they’re white? (b) How many more or less cigarettes does 40yearold smoke compared to a 39year old? (c) How many more or less cigarettes does a white person with 10 years of education smoke compared with a white person with 9 years of education? (d) Why did we include ageSq in the regression? What effect does it capture? (e) Interpret the coeﬃcient on logIncome . How does cigs change with income?...
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 Spring '09
 Woutersen
 Statistics, Econometrics, Regression Analysis, GDP Growth Rate, alternative hypotheses

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