Reference no: EM131112772

Question 1 - A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-years period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker.

Risk	Age	Blood Pressure	Smoker
12	57	152	0
24	67	163	0
13	58	155	0
56	86	177	1
28	59	196	0
51	76	189	1
18	56	155	1
31	78	120	0
37	80	135	1
15	78	98	0
22	71	152	0
36	70	173	1
15	67	135	1
48	77	209	1
15	60	199	0
36	82	119	1
8	66	166	0
34	80	125	1
3	62	117	0
37	59	207	1

a. Develop an estimated regression equation that can be used to predict the risk of stroke given the age and blood-pressure level.

b. Consider adding two independent variables to the model developed in part (a), one for (the interaction between age and blood-pressure level and the other for whether the person is a smoker. Develop an estimated regression equation using these four independent variables.

c. At a .05 level of significance, test to see whether the addition of the interaction term and the smoker variable contribute significantly to the estimated regression equation developed in part (a).

Question 2 - The National Football League rates prospects by position on a scale that ranges from 5 to 9. The ratings are interpreted as follows: 8-9 should start the first year; 7.0-7.9 should start; 6.0-6.9 will make the team as backup; and 5.0-5.9 can make the club and contribute. The following table shows the position, weight, time in seconds to run 40 yards, and ratings for 40 NFL prospects (USA Today, April 14, 2000).

Observation	Name	Position	Weight	Time	Rating
1	Peter Warrick	Wide receiver	194	4.53	9.0
2	Plaxico Burress	Wide receiver	231	4.52	8.8
3	Sylvester Morris	Wide receiver	216	4.59	8.3
4	Travis Taylor	Wide receiver	199	4.36	8.1
5	Laveranues Coles	Wide receiver	192	4.29	8.0
6	Dez White	Wide receiver	218	4.49	7.9
7	Jerry Porter	Wide receiver	221	4.55	7.4
8	Ron Dugans	Wide receiver	206	4.47	7.1
9	Todd Pinkston	Wide receiver	169	4.37	7.0
10	Dennis Northcutt	Wide receiver	175	4.43	7.0
11	Anthony Lucas	Wide receiver	194	4.51	6.9
12	Darrell Jackson	Wide receiver	197	4.56	6.6
13	Danny Farmer	Wide receiver	217	4.60	6.5
14	Sherrod Gideon	Wide receiver	173	4.57	6.4
15	Trevor Gaylor	Wide receiver	199	4.57	6.2
16	Cosey Coleman	Guard	322	5.38	7.4
17	Travis Claridge	Guard	303	5.18	7.0
18	Kaulana Noa	Guard	317	5.34	6.8
19	Leander Jordan	Guard	330	5.46	6.7
20	Chad Clifton	Guard	334	5.18	6.3
21	Manula Savea	Guard	308	5.32	6.1
22	Ryan Johanningmeir	Guard	310	5.28	6.0
23	Mark Tauscher	Guard	318	5.37	6.0
24	Blaine Saipaia	Guard	321	5.25	6.0
25	Richard Mercier	Guard	295	5.34	5.8
26	Damion McIntosh	Guard	328	5.31	5.3
27	Jeno James	Guard	320	5.64	5.0
28	Al Jackson	Guard	304	5.20	5.0
29	Chris Samuels	Offensive tackle	325	4.95	8.5
30	Stockar McDougle	Offensive tackle	361	5.50	8.0
31	Chris McIngosh	Offensive tackle	315	5.39	7.8
32	Adrian Klemm	Offensive tackle	307	4.98	7.6
33	Todd Wade	Offensive tackle	326	5.20	7.3
34	Marvel Smith	Offensive tackle	320	5.36	7.1
35	Michael Thompson	Offensive tackle	287	5.05	6.8
36	Bobby Williams	Offensive tackle	332	5.26	6.8
37	Darnell Alford	Offensive tackle	334	5.55	6.4
38	Terrance Beadles	Offensive tackle	312	5.15	6.3
39	Tutan Reyes	Offensive tackle	299	5.35	6.1
40	Greg Robinson-Ran	Offensive tackle	333	5.59	6.0

a. Develop dummy variables that will account for the player's position.

b. Develop an estimated regression equation to show how rating is related to position, weight, and time to run 40 yards.

c. At the .05 level of significance, test whether the estimated regression equation developed in part (b) represents a significant relationship between the independent variables and the dependent variable.

d. Is position a significant factor in the player's rating? Use a = .05. Explain.

Question 3 - A study investigated the relationship between audit delay (Delay), the length of time from a company's fiscal year-end to the date of the auditor s report, and variables that describe the client and the auditor. Some of the independent variables that were included in this study follow.

Industry - A dummy variable coded 1 if the firm was an industrial company or 0 if the firm was a bank, savings and loan, or insurance company.

Public - A dummy variable coded 1 if the company was traded on an organized exchange or over the counter; otherwise coded 0.

Quality  - A measure of overall quality of internal controls, as judged by the auditor, on a five-point scale ranging from "virtually none" (1) to "excellent" (5).

Finished - A measure ranging from 1 to 4, as judged by the auditor, where 1 indicates "all work performed subsequent to year-end" and 4 indicates "most work performed prior to year-end."

A sample of 40 companies provided the following data.

Delay	Industry	Public	Quality	Finished
62	0	0	3	1
45	0	1	3	3
54	0	0	2	2
71	0	1	1	2
91	0	0	1	1
62	0	0	4	4
61	0	0	3	2
69	0	1	5	2
80	0	0	1	1
52	0	0	5	3
47	0	0	3	2
65	0	1	2	3
60	0	0	1	3
81	1	0	1	2
73	1	0	2	2
89	1	0	2	1
71	1	0	5	4
76	1	0	2	2
68	1	0	1	2
68	1	0	5	2
86	1	0	2	2
76	1	1	3	1
67	1	0	2	3
57	1	0	4	2
55	1	1	3	2
54	1	0	5	2
69	1	0	3	3
82	1	0	5	1
94	1	0	1	1
74	1	1	5	2
75	1	1	4	3
69	1	0	2	2
71	1	0	4	4
79	1	0	5	2
80	1	0	1	4
91	1	0	4	1
92	1	0	1	4
46	1	1	4	3
72	1	0	5	2
85	1	0	5	1

a. Develop the estimated regression equation using all of the independent variables.

b. Did the estimated regression equation developed in part (a) provide a good fit? Explain.

c. Develop a scatter diagram showing Delay as a function of Finished. What does this scatter diagram indicate about the relationship between Delay and Finished?

d. On the basis of your observations about the relationship between Delay and Finished, develop an alternative estimated regression equation to the one developed in (a) to ex-plain as much of the variability in Delay as possible.

Detailed Question: I need these questions completed step by step using excel and the details on how to find the solutions.