1. A recent 10-year study conducted by a research team at the Great Falls Medical School was conducted to assess how age, systolic blood pressure, and smoking relate to the risk of strokes. Risk is interpreted as the probability (times 100) that the patient will have a stroke over the next 10-year period. For the smoking variable, define a dummy variable with 1 indicating a smoker and 0 indicating a nonsmoker.
   1. Develop an estimated multiple regression equation that relates risk of a stroke to the person's age, systolic blood pressure, and whether the person is a smoker.

Risk	Age	Pressure	Smoker
12	57	152	No
24	67	163	No
13	58	155	No
56	86	177	Yes
28	59	196	No
51	76	189	Yes
18	56	155	Yes
31	78	120	No
37	80	135	Yes
15	78	98	No
22	71	152	No
36	70	173	Yes
15	67	135	Yes
48	77	209	Yes
15	60	199	No
36	82	119	Yes
8	66	166	No
34	80	125	Yes
3	62	117	No
37	59	207	Yes

1. Is smoking a significant factor in the risk of stroke? Explain. Use a 0.05 level of significance.
2. What is the probability of a stroke over the next 10 years for Art Speen, a 68-year old smoker who has a systolic blood pressure of 175? What action might the physician recommend for this patient?

1. Johnson Filtration, Inc. provides maintenance service for water filtration systems throughout Southern Florida. Customers contact Johnson with requests for maintenance service on their water filtration systems. To estimate service time and the service cost, Johnson's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors: the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performs the repair (Donna Newton or Bob Jones). Data for a sample of 10 service calls are reported in the following table:

Repair Time in Hours	Months Since Last Service	Type of Repair	Repairperson
2.9	2	Electrical	Donna Newton
3.0	6	Mechanical	Donna Newton
4.8	8	Electrical	Bob Jones
1.8	3	Mechanical	Donna Newton
2.9	2	Electrical	Donna Newton
4.9	7	Electrical	Bob Jones
4.2	9	Mechanical	Bob Jones
4.8	8	Mechanical	Bob Jones
4.4	4	Electrical	Bob Jones
4.5	6	Electrical	Donna Newton

1. Develop the multiple regression equation to predict repair time, given the number of months since the last maintenance service, the repairperson and the type of repair.
2. What are the interpretations of the estimated regression parameters?
3. What does the coefficient of determination tell you about this model?

1. Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for the past 12 weeks:

Week	1	2	3	4	5	6	7	8	9	10	11	12
Actual Passenger Miles (in thousands)	17	21	19	23	18	16	20	18	22	20	15	22

1. Assuming an initial forecast for week 1 of 17,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use a smoothing constant of 0.2.
2. Present a table to compute the Tracking Signal for this problem.
3. Develop a Control Chart of the Tracking Signal using a control limit of +2.5 MAD.
4. For the forecast to be in control, what percentage of the errors must fall within + 2.5 MAD?
5. Is this forecast in control? Explain.