empir_ex04[1] - Chapter 4 Linear Regression with One...

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Chapter 4 Linear Regression with One Regressor ± Solutions to Empirical Exercises 1. (a)  AHE = 3.32 + 0.45 × Age Earnings increase, on average, by 0.45 dollars per hour when workers age by 1 year. (b) Bob’s predicted earnings = 3.32 + 0.45 × 26 = $11.70 Alexis’s predicted earnings = 3.32 + 0.45 × 30 = $13.70 (c) The R 2 is 0.02.This mean that age explains a small fraction of the variability in earnings across individuals. 2. (a) Course Evaluation Beauty Index -2 -1 0 1 2 2 3 4 5 There appears to be a weak positive relationship between course evaluation and the beauty index. (b)  _ Course Eval = 4.00 + 0.133 × Beauty . The variable Beauty has a mean that is equal to 0; the estimated intercept is the mean of the dependent variable ( Course_Eval ) minus the estimated slope (0.133) times the mean of the regressor ( Beauty ). Thus, the estimated intercept is equal to the mean of Course_Eval . (c) The standard deviation of
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This note was uploaded on 11/06/2009 for the course ECON ECON111 taught by Professor Smith during the Spring '09 term at Punjab Engineering College.

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empir_ex04[1] - Chapter 4 Linear Regression with One...

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