Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X₁ in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0=female and 1=male). The following is a partial result of computer output that was used on a sample of 20 individuals. ANOVA df SS MS F Regression 3 84 28 4 Residual 16 112 7 Total 19 196 Standard Error Predictor Coefficients of Coefficient Constant 21.00 0.70 X₁ 0.62 0.10 X2 0.92 0.19 X3 -0.51 0.92 a. Present the estimated regression equation and compute the coefficient of determination. Explain it. b. Use the t test to determine the significance of each independent variable. Let a = 0.05. (For each test, give the null and alternative hypotheses, test statistic, and conclusion.) c. Use the F test to determine whether or not the regression model is significant. Let a = 0.05. (For the test, give the null and alternative hypotheses, test statistic, and conclusion.) d. Does the estimated regression equation provide a good fit for the observed data? Explain it. e. Suppose a new person with X₁=40, X₂=4, X3-0. Use the estimated regression equation in part (a) to estimate the new person's income.