A B D E F Salary (RM) Industry Occupation Ed Ex 19388 6 45 49898 12 33 28219 12 12 83601 17 18 29736 8 47 50235 16 12 45976 12 43 9 33411 12 20 10 21716 12 11 11 37664 18 19 12 26820 18 33 13 29977 16 6 14 33959 17 26 15 11780 11 33 16 10997 14 0 17 17626 A O U O A U A O A U W A O - D W A N O A GI DI DI N N O A O W O O 12 45 o - o - 0 0 0 0 0 0 - 0 0 0 0 0 0 0 0 0 0 0 0 - 0 - 0 0 0 N 18 22133 16 10 19 21994 12 24 20 29390 13 18 21 32138 14 22 22 30006 16 27 23 68573 16 14 24 17694 8 38 25 26795 7 44 26 19981 4 54 27 14476 12 3 28 19452 13 3 29 28168 13 17 30 19306 34 31 13318 11 25 32 25166 12 10 Sheet1 +F G H A B D F 31 13318 25 32 25166 10 33 18121 18 34 13162 6 35 32094 14 36 16667 4 37 50171 39 38 31691 13 39 36178 40 40 15234 41 16817 26 42 22485 22 43 30308 10 44 11702 45 11186 0 46 12285 JO J D - A N A W O - D W - O A - O N A W W - W O DI W W O W A O 47 19284 3 N - 0 0 0 0 0 0 0 N - 6 6 6 - - 0 0 0 0 0 0 0 0 - 0 0 0 - - 48 11451 8 49 57623 31 25670 CO 50 51 83443 5 52 49974 26 53 46646 44 54 31702 12 39 55 13312 9 56 44543 18 10 57 15013 21 58 33389 22 59 60626 7 60 24509 14 15 61 20852 12 38 62 30133 10 27 Sheet1 +A B C D E F 61 20852 12 38 62 30133 10 27 63 31799 12 25 64 16796 12 14 65 20793 12 6 66 29407 10 19 67 29191 12 9 68 15957 10 69 34484 13 28 70 35185 14 12 71 26614 12 19 72 41780 12 9 73 55777 14 21 74 15160 8 45 75 66738 29 76 33351 16 4 77 33498 o o o o o o o o o o o o o - 0 0 0 0 0 0 0 - - 0 0 0 0 0 0 0 N 10 20 Co 78 29809 29 79 15193 12 15 80 23027 14 34 81 75165 15 12 82 18752 45 83 83569 18 29 84 32235 12 38 85 20852 12 1 86 13787 11 4 87 34746 14 15 88 17690 12 14 89 52762 18 7 90 60152 16 38 91 33461 16 7 92 13481 12 7 Sheet1 +\fQUESTION 1 (63 marks) A company is analyzing the salary of its staff as compared to other companies in the same state. Please refer to the attached secondary data (as given in TIMES). These variables are included in the dataset Salary(RM) Ed= Employee's years of education A Ex = Employee's years of working experience Part I (28 marks) (a) Draw an appropriate graph for the salary of the employees. Explain the graph briefly. [6 marks] (b) Based on the dataset given, obtain the descriptive statistics for the salary (in RM) and the employees' years of education. [6 marks] (c) Write a short report explaining the results obtained in part (b) above. Your report should include two measures of location and two measures of dispersion for EACH variable, description of the distribution as well as the best measures of location and dispersion. Units must be specified clearly in the report (marks will be deducted otherwise). [16 marks] Part II (20 marks) It is known that salary is influenced by the years of education. By using correlation and regression analysis in Excel: (a) Construct a scatter diagram showing this relationship. Identify the independent and the dependent variable clearly. Include the trend line in this diagram. Briefly explain the scatter diagram. [6 marks] (b) Generate a summary output. Construct the regression equation. Is the model significant? Explain. [8 marks] (c) Based on the output in part (b), interpret the y-intercept and the slope. Do you think the dependent variable is explained by the independent variable? [6 marks] Part III (15 marks) It is known that salary is also influenced by the years of working experience. Redo the regression analysis in Part II by including two independent variables - years of education and years of working experience. [3 marks] Based on the summary output answer the following: (a) construct the regression equation. [2 marks] (b) interpret the coefficients of the independent variables. (4 marks] (c) the significance of the overall model. [3 marks] (d) do you think the dependent variable is explained better in PART III comparing to PART II? Why? [3 marks]