Age at death	Mother's age at death	Father's age at death	No of years of employment	Gender
81	82	77	30	Female
66	80	63	35	Female
68	72	71	33	Female
72	71	66	30	Female
71	76	61	35	Female
62	65	57	36	Female
71	71	71	41	Female
67	68	68	25	Female
67	69	66	37	Female
79	88	73	20	Female
67	73	62	30	Female
71	76	67	25	Female
73	79	71	40	Female
72	66	75	40	Female
74	78	68	25	Female
74	82	66	20	Female
89	86	77	20	Female
83	90	72	20	Female
78	82	72	33	Female
71	78	64	40	Female
73	69	80	35	Female
74	79	71	35	Female
71	73	72	41	Female
77	72	72	20	Female
77	79	74	25	Female
74	77	64	15	Female
72	78	64	33	Female
77	85	77	18	Female
66	74	64	38	Female
70	67	65	38	Female
63	71	56	38	Female
82	83	78	25	Female
66	64	66	36	Female
74	76	66	35	Female
74	82	71	41	Male
77	85	69	31	Male
69	72	63	32	Male
72	77	69	40	Male
67	68	69	38	Male
74	71	76	45	Male
67	76	62	25	Male
68	74	62	30	Male
68	74	79	30	Male
71	71	60	28	Male
84	80	90	15	Male
78	82	70	40	Male
76	82	65	22	Male
68	71	61	35	Male
70	66	75	36	Male
77	82	76	30	Male
73	67	71	25	Male
72	78	70	30	Male
77	75	66	25	Male
75	73	69	30	Male
71	77	70	30	Male
70	77	60	41	Male
65	75	60	25	Male
68	72	66	31	Male
71	70	70	43	Male
68	75	63	32	Male
59	59	62	35	Male
83	82	82	30	Male
66	69	68	38	Male
76	80	70	31	Male
65	66	63	33	Male
70	66	68	25	Male
76	88	69	30	Male
74	79	70	25	Male
73	80	75	41	Male
75	76	72	25	Male
70	75	57	38	Male
80	84	75	18	Male
72	72	77	35	Male
80	74	77	20	Male
72	85	60	25	Male
72	73	69	33	Male
64	71	67	30	Male
73	88	63	30	Male
80	85	78	30	Male
72	78	64	30	Male

5. Based on the data set given above, perform a regression analysis and correlation analysis using excel, 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.

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.

f. 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