A researcher wonders whether males get paid more, on average, than females at a large firm. She interviews 50 employees and collects data on each employee's hourly wage (Wage in \$), years of higher education (Educ), years of experience (Exper), age (Age), and a Male dummy variable that equals 1 if male, 0 otherwise. A portion of the data is shown in the accompanying table. Click here for the Excel Data File a. Estimate: Wage =0+1 Educ +2 Exper +3 Age +4 Male +. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) b. Predict the hourly wage of a 41-year-old male and female employee with 9 years of higher education and 7 years experience. (Do not round intermediate calculations. Round final answers to 2 decimal places.) c-1. Interpret the estimated coefficient for Male. The male coefficient implies that males earn $1.79 per hour less than females at the firm, holding everything else the same. The male coefficient implies that males earn $1.79 per hour more than females at the firm, holding everything else the same. The male coefficient implies that males earn $0.08 per hour more than females at the firm, holding everything else the same. The male coefficient implies that males earn $0.08 per hour less than females at the firm, holding everything else the same. c-2. Is the variable Male significant at the 5% level? Do the data suggest that sex discrimination exists at this firm? Yes, since we reject the null hypothesis of discrimination. Yes, since we reject the null hypothesis of no discrimination. No, since we do not reject the null hypothesis of discrimination. No, since we do not reject the null hypothesis of no discrimination