bachelor's degree. The workers' ages ranged from 25 to 34 years. The data set also contains information on the region of the country where the person lived, marital status, and number of children. Let...

Extracted text: bachelor's degree. The workers' ages ranged from 25 to 34 years. The data set also contains information on the region of the country where the person lived, marital status, and number of children. Let AHE=average hourly earnings College=binary variable (1 if college, O if high school) Female-binary variable (1 if female, O if high male) Age-age in years Northeast-binary variable (1 if Region=Northeast, O otherwise) Midwest-binary variable (1 if Region=Midwest, O otherwise) South=binary variable (1 if Region=South, O otherwise) West-binary variable (1 if Region=West, O otherwise) Results of Regressions of Average Hourly Earnings on Sex and Education Binary Variables and Other Characteristics Using 2015 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) College (X;) 10.47 (0.29) 10.44 (0.29) 10.42 (0.29) Female (X) -4.56 (1.29) -4.57 (0.29) -4.69 (0.29) Age (X) 0.61 (0.06) (0.06) Northeast (N) 0.74 (047) Midwest (X) -1.54 (0.40) South (X) 0.44 (0.37) Intercept 18.15 0.11 0.33 (1.47) (0.19) (1.46) Summary Statistics and Joint Tests F-statistic testing regional effects = 0 9.32 SER 12.15 12.03 12.01 R a165 0.182 0.185 7178 7178 7178 Use the regression results in column (3): Juanita is a 28-year-old female college graduate from the South. Molly is a 28-year-old female college graduate from the West. Construct a 95% confidence interval for the difference in expected earnings between Juanita and Molly. O 1-4.33, 4.33] O 1.41, 2.831 O 19.90, 11.041 O -1.17, 0.29]