Question
Observation No Age at death Mother's age at death Father's age at death No of years of employment Gender 16 81 82 77 30 Female
Observation No | Age at death | Mother's age at death | Father's age at death | No of years of employment | Gender |
16 | 81 | 82 | 77 | 30 | Female |
17 | 66 | 80 | 63 | 35 | Female |
18 | 68 | 72 | 71 | 33 | Female |
19 | 72 | 71 | 66 | 30 | Male |
20 | 71 | 76 | 61 | 35 | Female |
21 | 62 | 65 | 57 | 36 | Female |
22 | 71 | 71 | 71 | 41 | Female |
23 | 67 | 68 | 68 | 25 | Female |
24 | 67 | 69 | 66 | 37 | Female |
25 | 79 | 88 | 73 | 20 | Male |
26 | 67 | 73 | 62 | 30 | Male |
27 | 71 | 76 | 67 | 25 | Male |
28 | 73 | 79 | 71 | 40 | Male |
29 | 72 | 66 | 75 | 40 | Male |
30 | 74 | 78 | 68 | 25 | Female |
31 | 74 | 82 | 66 | 20 | Male |
32 | 89 | 86 | 77 | 20 | Male |
33 | 83 | 90 | 72 | 20 | Female |
34 | 78 | 82 | 72 | 33 | Male |
35 | 71 | 78 | 64 | 40 | Female |
36 | 73 | 69 | 80 | 35 | Male |
37 | 74 | 79 | 71 | 35 | Female |
38 | 71 | 73 | 72 | 41 | Female |
39 | 77 | 72 | 72 | 20 | Male |
40 | 77 | 79 | 74 | 25 | Male |
41 | 74 | 77 | 64 | 15 | Male |
42 | 72 | 78 | 64 | 33 | Male |
43 | 77 | 85 | 77 | 18 | Male |
44 | 66 | 74 | 64 | 38 | Female |
45 | 70 | 67 | 65 | 38 | Female |
46 | 63 | 71 | 56 | 38 | Female |
47 | 82 | 83 | 78 | 25 | Female |
48 | 66 | 64 | 66 | 36 | Male |
49 | 74 | 76 | 66 | 35 | Male |
50 | 74 | 82 | 71 | 41 | Male |
51 | 77 | 85 | 69 | 31 | Male |
52 | 69 | 72 | 63 | 32 | Female |
53 | 72 | 77 | 69 | 40 | Male |
54 | 67 | 68 | 69 | 38 | Female |
55 | 74 | 71 | 76 | 45 | Male |
56 | 67 | 76 | 62 | 25 | Male |
57 | 68 | 74 | 62 | 30 | Female |
58 | 68 | 74 | 79 | 30 | Female |
59 | 71 | 71 | 60 | 28 | Male |
60 | 84 | 80 | 90 | 15 | Male |
61 | 78 | 82 | 70 | 40 | Male |
62 | 76 | 82 | 65 | 22 | Female |
63 | 68 | 71 | 61 | 35 | Female |
64 | 70 | 66 | 75 | 36 | Female |
65 | 77 | 82 | 76 | 30 | Male |
66 | 73 | 67 | 71 | 25 | Male |
67 | 72 | 78 | 70 | 30 | Male |
68 | 77 | 75 | 66 | 25 | Male |
69 | 75 | 73 | 69 | 30 | Female |
70 | 71 | 77 | 70 | 30 | Male |
71 | 70 | 77 | 60 | 41 | Female |
72 | 65 | 75 | 60 | 25 | Female |
73 | 68 | 72 | 66 | 31 | Female |
74 | 71 | 70 | 70 | 43 | Female |
75 | 68 | 75 | 63 | 32 | Female |
76 | 59 | 59 | 62 | 35 | Female |
77 | 83 | 82 | 82 | 30 | Male |
78 | 66 | 69 | 68 | 38 | Male |
79 | 76 | 80 | 70 | 31 | Male |
80 | 65 | 66 | 63 | 33 | Male |
81 | 70 | 66 | 68 | 25 | Female |
82 | 76 | 88 | 69 | 30 | Male |
83 | 74 | 79 | 70 | 25 | Male |
84 | 73 | 80 | 75 | 41 | Male |
85 | 75 | 76 | 72 | 25 | Male |
86 | 70 | 75 | 57 | 38 | Female |
87 | 80 | 84 | 75 | 18 | Male |
88 | 72 | 72 | 77 | 35 | Male |
89 | 80 | 74 | 77 | 20 | Male |
90 | 72 | 85 | 60 | 25 | Male |
91 | 72 | 73 | 69 | 33 | Male |
92 | 64 | 71 | 67 | 30 | Female |
93 | 73 | 88 | 63 | 30 | Male |
94 | 80 | 85 | 78 | 30 | Male |
95 | 72 | 78 | 64 | 30 | Male |
Based on the data set you extracted, perform a regression analysis and correlation analysis, and answer the questions given below.
a. Interpret the meaning of all the coefficients in the regression equation.
b. Interpret the calculated coefficient of determination and the standard error of the estimate
c. At 5% significance level, test the overall model significance. (2 marks) d. At 5% significance level, assess the significance of independent variables in the model.
e. Based on the correlation coefficients in the correlation output, assess the correlation between explanatory variables and check the possibility of multicollinearity.
Assuming that you are the actuary, help this insurance company to make policy decisions on insurance premiums. Your suggestions should be based on the above findings. You can propose to them to gather more evidence if there are important variables omitted in the above model.
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