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Using the regression results in column (3): a. Do there appear to be important regional differences? Use an appropriate hypothesis test to explain your answer. b. Juanita is a 28-year-old female college graduate from the South. Molly is a 28-year-old female college graduate from the West. Jennifer is a 28-year-old female college graduate from the Midwest. i. Construct a 95% confidence interval for the difference in expected earnings between Juanita and Molly. ii. Explain how you would construct a 95% confidence interval for the difference in expected earnings between Juanita and Jennifer. (Hint: What would happen if you included West and excluded Midwest from the regression?)

Using the regression results in column (3): a. Do there appear to be important regional differences? Use an appropriate hypothesis test to explain your answer. b. Juanita is a 28-year-old female college graduate from the South. Molly is a 28-year-old female college graduate from the West. Jennifer is a 28-year-old female college graduate from the Midwest. i. Construct a 95% confidence interval for the difference in expected earnings between Juanita and Molly. ii. Explain how you would construct a 95% confidence interval for the difference in expected earnings between Juanita and Jennifer. (Hint: What would happen if you included West and excluded Midwest from the regression?)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Using the regression results in column (3):
a. Do there appear to be important regional differences? Use an appropriate hypothesis test to explain your answer.
b. Juanita is a 28-year-old female college graduate from the South. Molly
is a 28-year-old female college graduate from the West. Jennifer is a
28-year-old female college graduate from the Midwest.
i. Construct a 95% confidence interval for the difference in expected
earnings between Juanita and Molly.
ii. Explain how you would construct a 95% confidence interval for
the difference in expected earnings between Juanita and Jennifer.
(Hint: What would happen if you included West and excluded
Midwest from the regression?)

Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using 2012 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) College (X1) 8.31 (0.23) 8.32 (0.22) 8.34 (0.22) Female (X2) -3.85 (0.23) -3.81 (0.22) -3.80 (0.22) 0.51 (0.04) 0.52 (0.04) Age (X3) 0.18 (0.36) Northeast (X4) -1.23 (0.31) Midwest (Xs) -0.43 (0.30) South (X6) 17.02 (0.17) 1.87 (1.18) 2.05 (1.18) Intercept Summary Statistics and Joint Tests 7.38 F-statistic for regional effects = 0 9.79 9.68 9.67 SER 0.162 0.180 0.182 R2 7440 7440 7440
Transcribed Image Text:Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using 2012 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) College (X1) 8.31 (0.23) 8.32 (0.22) 8.34 (0.22) Female (X2) -3.85 (0.23) -3.81 (0.22) -3.80 (0.22) 0.51 (0.04) 0.52 (0.04) Age (X3) 0.18 (0.36) Northeast (X4) -1.23 (0.31) Midwest (Xs) -0.43 (0.30) South (X6) 17.02 (0.17) 1.87 (1.18) 2.05 (1.18) Intercept Summary Statistics and Joint Tests 7.38 F-statistic for regional effects = 0 9.79 9.68 9.67 SER 0.162 0.180 0.182 R2 7440 7440 7440
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