3 Perform a regression analysis using compa as the dependent variable and the same independent variables as used in question 2. Show the result, and interpret your findings by answering the same questions. Note: be sure to include the appropriate hypothesis statements. Regression hypotheses Ho: Ha: Coefficient hyhpotheses (one to stand for all the separate variables) Ho: Ha: Place D94 in output box. Interpretation: For the Regression as a whole: What is the value of the F statistic: What is the p-value associated with this value: Is the p-value < 0.05? Do you reject or not reject the null hypothesis: What does this decision mean for our equal pay question: For each of the coefficients: What is the coefficient's p-value for each of the variables: Is the p-value < 0.05? Do you reject or not reject each null hypothesis: What are the coefficients for the significant variables? Using only the significant variables, what is the equation? Is gender a significant factor in compa: If so, who gets paid more with all other things being equal? How do we know? Intercept Compa = Midpoint Age Perf. Rat. Service Gender Degree ID Salary Compa Midpoint Age 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 56.5 28.3 34 64.5 46.6 75.6 41.6 24.6 74.6 24 24.3 57.9 41.9 24.5 23.1 41.1 71.8 34.2 23.8 34.3 78.5 54.9 23.3 55.9 23.7 23.8 38.7 76.7 75.9 48.5 22.3 27 61.4 27.8 22.8 24.7 23.3 56.8 36.1 24 47.3 21.9 75.6 57.2 53.1 58.1 61 64.6 66.3 57.5 0.992 0.913 1.097 1.132 0.971 1.129 1.040 1.070 1.114 1.044 1.055 1.015 1.047 1.066 1.005 1.027 1.259 1.104 1.036 1.106 1.171 1.143 1.015 1.165 1.029 1.036 0.967 1.145 1.133 1.011 0.970 0.871 1.077 0.898 0.992 1.075 1.014 0.997 1.165 1.045 1.182 0.950 1.128 1.003 1.107 1.019 1.071 1.134 1.163 1.008 57 31 31 57 48 67 40 23 67 23 23 57 40 23 23 40 57 31 23 31 67 48 23 48 23 23 40 67 67 48 23 31 57 31 23 23 23 57 31 23 40 23 67 57 48 57 57 57 57 57 34 52 30 42 36 36 32 32 49 30 41 52 30 32 32 44 27 31 32 44 43 48 36 30 41 22 35 44 52 45 29 25 35 26 23 27 22 45 27 24 25 32 42 45 36 39 37 34 41 38 Performance Rating 85 80 75 100 90 70 100 90 100 80 100 95 100 90 80 90 55 80 85 70 95 65 65 75 70 95 80 95 95 90 60 95 90 80 90 75 95 95 90 90 80 100 95 90 95 75 95 90 95 80 Service Gender Raise Degree Gender1 Gr 8 7 5 16 16 12 8 9 10 7 19 22 2 12 8 4 3 11 1 16 13 6 6 9 4 2 7 9 5 18 4 4 9 2 4 3 2 11 6 2 5 8 20 16 8 20 5 11 21 12 0 0 1 0 0 0 1 1 0 1 1 0 1 1 1 0 1 1 0 1 0 1 1 1 0 1 0 1 0 0 1 0 0 0 1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 0 5.7 3.9 3.6 5.5 5.7 4.5 5.7 5.8 4 4.7 4.8 4.5 4.7 6 4.9 5.7 3 5.6 4.6 4.8 6.3 3.8 3.3 3.8 4 6.2 3.9 4.4 5.4 4.3 3.9 5.6 5.5 4.9 5.3 4.3 6.2 4.5 5.5 6.3 4.3 5.7 5.5 5.2 5.2 3.9 5.5 5.3 6.6 4.6 0 0 1 1 1 1 1 1 1 1 1 0 0 1 1 0 1 0 1 0 1 1 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 M M F M M M F F M F F M F F F M F F M F M F F F M F M F M M F M M M F F F M F M M F F M F M M F M M E B B E D F C A F A A E C A A C E B A B F D A D A A C F F D A B E B A A A E B A C A F E D E E E E E The ongoing question that the weekly assignments will focu Note: to simplfy the analysis, we will assume that jobs with The column labels in the table mean: ID - Employee sample number Age - Age in years Service - Years of service (rounded) Midpoint - salary grade midpoint Grade - job/pay grade Gender1 (Male or Female) Salary - Salar Performance Gender - 0 = Raise - perce Degree (0= B Compa - salar us on is: Are males and females paid the same for equal work (under the Equal Pay Act)? hin each grade comprise equal work. ry in thousands Rating - Appraisal rating (employee evaluation score) male, 1 = female ent of last raise BS\\BA 1 = MS) ry divided by midpoint