Maximizing Revenue: Solving a Probability Problem in Statistics and Probability

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In summary, an airline charges each passenger $300 for a trip between City A and City B. The airplane holds exactly 100 passengers. Each passenger has 70% probability of showing up, independent of the other passengers. All tickets can be rebooked for a later flight at no extra charge, so the airline cannot penalize a no-show passenger. However, if they book too many people and more than 100 show up, the airline has to pay $500 to each passenger who is denied passage on that flight. For example, if they book 300 people and all 300 show up, they actually lose money: $300×300−$500×200=−$10,000. The airline should book somewhat more than 100 passengers in order
  • #1
Lionheart3388
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Hi this is a problem I had in statistics and probability. It may actually be very simple, but it just seems like I did way too little work. Thanks for the help!


Homework Statement



An airline charges each passenger $300 for a trip between City A and City B. The airplane holds exactly 100 passengers. Each passenger has 70% probability of showing up, independent of the other passengers. All tickets can be rebooked for a later flight at no extra charge, so the airline cannot penalize a no-show passenger. Clearly, the airline should book somewhat more than 100 passengers because if they do not overbook somewhat, they will make on average $300×70 = $21,000 per flight, while if the plane were completely full, they would make $30,000 per flight. However, if they book too many people and more than 100 show up, the airline has to pay $500 to each passenger who is denied passage on that flight. For example, if they book 300 people and all 300 show up, they actually lose money: $300×300 − $500×200 = −$10,000.
How many additional passengers (beyond 100) should they book in order to maximize their mean revenue? Although this problem can be solved with JMP, you are not required to use JMP for it. You may use any methods and/or software you wish. The number of passengers who show up follows a binomial probability model. However, the associated random variable is not just $300 times the number of passengers.


Homework Equations



P(X=x)=nCx p^x q^(n-x)
mean=np
SD=root(npq)
q=1-p

The Attempt at a Solution


I assumed that using a binomial distribution, having a mean of 100 passengers would result in maximum revenue, so 100=np=n*.70, resulting in n=143, but this seems too easy.
 
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  • #2
You're right. It was too easy. Your assumption, while plausible, turns out not to be correct. I'm not sure how to solve it analytically, but it's pretty straightforward to solve numerically.
 
  • #3
Ok thanks. I actually think I got the answer basically brute forcing it.
 
  • #4
I think we have to found for which value of n>=100 we get the maximum of

[tex]\sum_{x=1}^{n}{300xP(X=x)}-\sum_{x=101}^{n}{500(x-100)P(X=x)}[/tex]

Have to make a computer program or use a math software like MATLAB to find it.
 

Related to Maximizing Revenue: Solving a Probability Problem in Statistics and Probability

What is the concept of maximizing revenue?

Maximizing revenue is the process of finding the most efficient and effective way to increase the amount of money a business or organization brings in. This can involve analyzing data, developing strategies, and making decisions to optimize profits.

How does statistics and probability play a role in maximizing revenue?

Statistics and probability are important tools in maximizing revenue as they help identify patterns, trends, and probabilities that can guide decision-making. By analyzing data and using probability calculations, businesses can make informed decisions about pricing, marketing, and other strategies to increase revenue.

What is the probability problem in maximizing revenue?

The probability problem in maximizing revenue typically involves calculating the likelihood of a certain outcome or event occurring, and using that information to make decisions about pricing, marketing, and other strategies. For example, a business may use probability to determine the optimal price point for a product that will maximize profits.

What are some common techniques for solving probability problems in maximizing revenue?

Some common techniques for solving probability problems in maximizing revenue include using probability distributions, simulation models, and regression analysis. These methods can help identify patterns and trends, and make predictions about future outcomes to inform decision-making.

What are the potential benefits of effectively maximizing revenue?

The potential benefits of effectively maximizing revenue include increased profits, improved financial stability, and a competitive advantage in the market. It can also lead to better resource management and strategic decision-making, which can benefit the overall success and growth of a business or organization.

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