Airline Problem with Poisson Approximation

In summary, an ailrine always overbooks if possible. The airline can expect to pay $598.56 in total payout to passengers who cannot get on the flight.
  • #1
mutzy188
37
0

Homework Statement



An ailrine always overbooks if possible. A particular plane ha 95 seats on a flight in which a ticket sells for $300. The airline sells 100 such tickets for this flight. Use a Poisson approximation only.

(a) If the probbility of an individual not showing is 0.05, assuming independence, what is the probability that the airline can accomidate all the passengers who do show up?

(b) If the airline must return the $300 price plus a penalty of $400 to each passenger that cannot get on the flight, what is the expected payout (penalty plus ticket refund) that the airline will pay? Answer = $598.56

The Attempt at a Solution



I know how to do part (a), and I got 0.560 as my answer, which agrees with the answer in the back of the book. I just don't know how to do part b.

My thoughts:

The probability that they cannot accomidate the passengers = 1 - .56 = 0.44.
(0.44)(400) + 300 = $476 . . . . but that's not correct. So I don't know what to do for this part. Any help would be greatly appreciated.

Thanks
 
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  • #2
You need to compute the expected number of passengers that will not show up, and multiply by $700.
 
  • #3
Avodyne said:
You need to compute the expected number of passengers that will not show up, and multiply by $700.

How do I find the expected number of passengers that will not show up?
 
  • #4
Sorry, that was a little too simplistic. If 5 or more fail to show up, there is no payout. If n fail to show up, with n<5, then the payout is $700 times 5-n. So if Pn is the probability that n people fail to show up, you need to compute (5-n)Pn summed over n from 0 to 4.
 
  • #5
Well, I just did the calculation, using Poisson probabilities, and I got $614.14. Then I tried it using the more accurate binomial probabilities, and then I got $598.56, which is your book's answer. But the problem tells you to use Poisson. So your book screwed up.
 
  • #6
Thanks for your help :smile:
 

1. What is the "Airline Problem with Poisson Approximation"?

The "Airline Problem with Poisson Approximation" is a mathematical model used to predict the number of customers that will arrive at an airline check-in counter during a specific time period. It is based on the Poisson distribution, which is commonly used to model the probability of rare events occurring in a given time frame.

2. How is the Poisson distribution used in this problem?

The Poisson distribution is used to calculate the probability of a certain number of customers arriving at the airline check-in counter in a given time period. It takes into account the average arrival rate of customers and calculates the likelihood of different numbers of customers arriving.

3. What factors are considered in this problem?

The "Airline Problem with Poisson Approximation" takes into account the average arrival rate of customers, the length of the time period, and the probability of a customer arriving during that time period. It also assumes that customer arrivals are independent of each other and occur randomly.

4. How accurate is the Poisson approximation in this problem?

The accuracy of the Poisson approximation in the "Airline Problem with Poisson Approximation" depends on the assumptions made and the specific parameters used in the model. In general, it is a good approximation when the average arrival rate is low and the time period is relatively short.

5. What other applications can the Poisson distribution be used for?

The Poisson distribution has many other applications in addition to the "Airline Problem with Poisson Approximation". It is commonly used in fields such as finance, insurance, and healthcare to model rare events such as accidents, natural disasters, and disease outbreaks. It is also used in quality control to monitor defect rates and in telecommunications to predict call arrival rates.

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