A manager is trying to determine whether there is a relation between sales district and product sales

Question 1

A manager is trying to determine whether there is a relation between sales district and product sales (I000,s units). He has the data below:

District	Electric Fork	Back Scratcher	Husband Whacker
North	27	68	98
East	35	90	56
West	56	35	34
South	45	36	23

Is there a relationship between the type of product sold and the district?
Which products should be emphasized in which areas?
Why are expected values important in this type of analysis?

Question 2

Prof. Bumble is a statistics professor at a large private university in FL. He often forgets where he has parked his car and has to be escorted there by the university security staff. He has been there a long time and Dr. Jekyll of the medical staff has noticed that as Prof. Bumble gets older the number of times he loses his car increases. Dr. Jekyll has collected the following data from security records.

Prof. Bumble’s age # times looses car/year

Is Professor Bumble getting more forgetful with age?
What would the prediction be for times forgetting his car that you would make should Prof. Bumble continue to 70 years old?
Would the prediction in b) be valid? Why or why not?
How much of the variance in times losing car can be accounted for by his age?

Question 3

The Philadelphia Eagles would like to know what motivates fans to attend the games. Coach Andy Reid has gathered data on attendance, Eagles and Opponents win/loss percentage, number of games played, temperature, and whether or not his troublesome wide receiver Terrell Owens has committed some atrocity (example, called QB Donovan McNabb an idiot or some asinine public display) in the week before the game (1 = yes, 0 = no).

Game Number	Game Attendance	Team Win/Loss Percentage	Opponent Win/Loss Percentage	Games Played	Temperature	TO Outburst
1	54,502	33.3	80	6	47	1
2	52,459	25	50	4	56	0
3	55,600	80	66.6	5	55	1
4	56,780	75	100	8	60	1
5	54,600	60	80	10	55	0
6	59,300	100	60	10	49	1
7	54,603	66.6	25	3	67	0
8	55,789	50	50	6	55	0
9	57,800	80	40	10	53	1
10	59,450	75	100	8	48	1
11	53,890	20	75	5	65	0
12	55,097	70	70	10	56	0
13	57,666	83.3	66.6	6	60	1
14	52,500	20	20	5	59	0
15	56,780	80	100	8	46	1
16	57,543	80	70	10	50	1

Does the Eagles win/loss percentage count?
Does TO’s behavior count? If so how much? Should the team dump him for attendance causes?
Is multi-co linearity a problem in this analysis?
What would be the 95% confidence interval for an attendance prediction be when the Eagles had won 75% of their games, their opponents had won 50%, they had played 8 games, the temperature was 49 degrees and TO had said earlier in the week that both Reed and Donovan should be sent to Iraq.

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