The data presented is the results of a 4-year study conducted to assess how age, weight, and gender influence the risk of diabetes. Risk is interpreted as the probability (times 100) that the patient will have diabetes over the next 4-year period.

1. What predictive model you suggest to relate risk of diabetes to the persons age, weight and the gender. Why? (you dont need to build the model just explain). (4 marks)
2. Develop an estimated multiple regression model that relates the expected remaining life to the persons age, weight, gender, life style and risk of diabete. Present the regression formula as a mathematical equation. Interpret the coefficients of the regression and comment on the strength of the regression. (4 marks)
3. What is the expected remaining life for a 59-year-old man living in a small town with 72 kg weight and risk of 25% of diabete? (4 marks)

Age	Weight (Kg)	Gender	Life style	Risk (%)	Expected remaining life
56	80	Female	Small town	40	3.96
27	79	Male	Big city	23	6.17
80	85	Female	Country	67	2.60
91	91	Female	Small town	71	2.75
59	67	Male	Big city	45	4.27
74	84	Female	Country	54	2.54
56	81	Female	Small town	48	3.03
73	68	Male	Small town	49	3.71
83	82	Female	Big city	65	2.34
81	69	Male	Big city	59	2.77
74	71	Male	Big city	56	3.34
73	80	Female	Small town	59	2.23
70	77	Male	Country	46	3.38
80	97	Female	Big city	64	2.48
63	59	Male	Country	39	4.97
85	102	Female	Big city	73	2.04
69	87	Male	Small town	63	2.68
83	98	Male	Big city	87	2.47
65	85	Female	Country	52	2.97
62	95	Male	Big city	61	2.97
79	69	Male	Big city	59	2.35
57	77	Female	Small town	46	3.30
81	51	Male	Big city	64	2.79
72	60	Male	Country	64	2.67