Before banks issue a credit card, they usually rate or score the customer in terms of his or her projected probability of being a profitable customer. A typical scoring table appears below.

The score is the sum of the points on the six items. For example, Sushi Brown is under 25 years old (12 pts.), has lived at the same address for 2 years (0 pts.), owns a 4-year-old car (13 pts.), with car payments of $75 (6 pts.), housing cost of $200 (10 pts.), and a checking account (3 pts.). She would score 44.
A second chart is then used to convert scores into the probability of being a profitable customer. A sample chart of this type appears below.

Sushi’s score of 44 would translate into a probability of being profitable of approximately .81. In other words, 81% of customers like Sushi will make money for the bank card operations.
Here are the interview results for three potential customers.

1. Score each of these customers and estimate their probability of being profitable.
2. What is the probability that all three are profitable?
3. What is the probability that none of them are profitable?
4. Find the entire probability distribution for the number of profitable customers among this group of three.
5. Write a brief summary of yourfindings.

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Under 25 25-29 (12 pts) (5 pts 35+ pts 18 pts.) Time at 1-2 yrs. 3-4 yrs. + yrs. same (9pts.) (0 pts.13 pts) (20 pts.) address Auto age None Monthly None $1-$99 $100-$299 $300+ payment 0-1yr 2-4 yrs. 5yrs (18 pts) 12 pts (13 pts.) 3 pts.) (15 pts.) 6 pts 4 pts 0pts.) Housing $1-$199 $200-$399 Owns cost Lives witlh (0 pts.) (10 pts (12 pts) relatives 24 pts.) Checking/ Both Checking Savings Neither savings on accounts 15 pts.) (3 pts. 2 pts.) 0 pts.) 30 | 40 | 50 | 60 | 70 | 80 | 90 Score Probability 7078 85 90 94 9596 David Edward Bom Brendan McLaughlin 42 Ann Name Age Time at same address Auto age Monthly car payment Housing cost Checking/savings accounts 23 S140 99 $300 $200 wns clear Both $175 Checking only Neither