c) Suppose the correlation coefficient is -0.4. What percentage of the total variation in salary can be explained by gender? 2. It is argued that it is not fair to investigate the effect that gender has on salaries without also considering the years of experience. So the following regression model is considered: Y = Bo + BiXin + B2X2 +i where Y is the monthly salary; X = 0 if male and 1 if female; and X2 is the years of experience. This can also be written in matrix form as Y X + E. The following results were obtained when the above model was fitted: 0.5 0 0 (X'X)-1= 0 0.2 0 200 0 0.005 ANOVA Sum of Squares DF Mean Square F Regression 7.50 2 Residual 3.15 17 3.750 0.185 20.24 Total 10.65 19 Parameter Estimates model Beta (Intercept) 5.86 Gender -0.49 Experience 0.18 a) What is the regression line for the male employees? In blackboard: i) Enter the Y-intercept (two decimal places) ii) Enter the slope (two decimal places)