Is Overbooking Probability Calculated Correctly?

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  • Thread starter mathmari
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In summary, the conversation discusses the concept of overbooking in the airline industry. It is assumed that 5% of passengers will not appear for their flight, so the airline sells 52 tickets for a flight with 50 seats. The probability of a passenger not appearing is calculated, and the correct method for calculating the probability of the flight being overbooked is explained. The conversation also clarifies the assumption of independence between events.
  • #1
mathmari
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MHB
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Hey! :eek:

I am looking at the following:

An airline assumes that $5 \%$ of all passengers that have booked for a flight will not appear for departure. They therefore book a flight with $50$ seats by selling $52$ tickets. It is assumed that one passenger independently of the other cancels his flight.Do we model the facts as a probability space as follows?

$\Omega=\{(x_1, \ldots , x_{52}) \mid x_i\in \{0,1\}\}$

$x_i=\left\{\begin{matrix}
1, & \text{ appears } \\
0, & \text{ does not appear }
\end{matrix}\right.$

A="Overbooking"
$A=\{(x_1, \ldots , x_{52})\in \Omega\mid \sum_{i=1}^{52}b_i\geq 51\}$

(Wondering)
In this case we have Bernoulli process of length $52$, since we are just interested whether an event occurs or not, i.e., if a passenger appers or not. For the single experiment, there are only two possible results. The single experiment is repeated $ 52 $ times independently of each other, since $52$ tickets are selled and it holds that a passenger independently of the other cancels his flight. We are also not interested which passenger doesn't appear but how many. From all these it follows that we have a Bernoulli process. Is this correct? (Wondering) We consider "Success" that a passenger doesn't appear. The propability that teh Success occurs, i.e., that a passenger doen;t appear, is always the same and equal to $5\%$. I want to calculate the probability that $k$ passengers don't appear, where $k\in \{0,1, \ldots , 52\}$.

I have done the following:
The probability that $k$ passengers don't appear, i.e. that we have exactly $k$ times Success, is equal to:
\begin{equation*}B(52;0,05;k)=\binom{52}{k}\cdot (0,05)^k\cdot (1-0,05)^{52-k}=\binom{52}{k}\cdot (0,05)^k\cdot (0,95)^{52-k}\end{equation*}

Is that correct? (Wondering) Then I want to calculate the probability that a passenger cannot take the flight although he has a ticket.
Does this mean that exacttly one passenger cannot take the flight, although it has a ticket or at least one passenger? (Wondering)

If it is meant exactly one, we want to calculate the probability that $51$ appear, i.e. that one passenger doesn't appear.
This probability is equal to
\begin{align*}B(52;0,05;1)&=\binom{52}{1}\cdot (0,05)^1\cdot (1-0,05)^{52-1}=\frac{52!}{1!\cdot (52-1)!}\cdot 0,05\cdot (0,95)^{51}=\frac{51!\cdot 52}{1!\cdot 51!}\cdot 0,05\cdot (0,95)^{51} \\ & = 52\cdot 0,05\cdot (0,95)^{51}=2,6\cdot (0,95)^{51}\approx 0,19=19\%\end{align*}

If it meant at least one, we want to calculate the probability that $52$ or $51$ passengers appear, i.e., that $0$ or $1$ passenger doesn't appear.
This probability is equal to
\begin{align*}B(52;0,05;0)+B(52;0,05;1)&=\binom{52}{0}\cdot (0,05)^0\cdot (1-0,05)^{52-0}+\binom{52}{1}\cdot (0,05)^1\cdot (1-0,05)^{52-1} \\ & =\frac{52!}{0!\cdot (52-0)!}\cdot 1\cdot (0,95)^{52}+\frac{52!}{1!\cdot (52-1)!}\cdot 0,05\cdot (0,95)^{51} \\ & =\frac{52!}{1\cdot 52!}\cdot (0,95)^{52}+\frac{51!\cdot 52}{1!\cdot 51!}\cdot 0,05\cdot (0,95)^{51} \\ & =1\cdot (0,95)^{52}+ 52\cdot 0,05\cdot (0,95)^{51} \\ & =(0,95)^{52}+ 2,6\cdot (0,95)^{51} \\ & \approx 0,07+ 0,19 \\ & =0,26=26\% \end{align*}

Are both cases correct? (Wondering) At a suggested solution there is the following:
\begin{align*}P("\text{Overbooking}")&=P(52 \text{ apprear })\cup P(51 \text{ apprear }) \\ & = 1-\binom{52}{0}\cdot (0,05)^0\cdot (0,95)^{52}+1-\binom{52}{1}\cdot (0,05)^1\cdot (0,95)^{51} \\ & = 1-(1\cdot 1\cdot 0,95^{52})+1-(52\cdot 0,05\cdot (0,95)^{51}) \\ & = 0,259496\end{align*}

Is this the same as I did? Why do we take here 1-B(52;0,05;0) and 1-B(52;0,05;1) ? (Wondering)
 
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  • #2
Hey mathmari! (Smile)

That looks all correct. (Nod)
The calculation of the suggested solution is wrong.
This becomes clear when we verify that calculation. The final answer does not match.
Their initial formula and final answer are correct, but the calculation in between is not. (Nerd)
 
  • #3
I like Serena said:
That looks all correct. (Nod)

Great! (Happy)
I like Serena said:
The calculation of the suggested solution is wrong.
This becomes clear when we verify that calculation. The final answer does not match.
Their initial formula and final answer are correct, but the calculation in between is not. (Nerd)

What exactly is wrong at the suggested solution? (Wondering)
 
  • #4
mathmari said:
Great! (Happy)

What exactly is wrong at the suggested solution? (Wondering)

It calculates $P(\lnot (52 \text{ appear})) + P(\lnot (51 \text{ appear}))$.
It's a halfway effort to calculate $P(\text{not overbooked})$.
Properly it should be:
$$P(\text{not overbooked}) = P(\lnot (52 \text{ appear}) \land \lnot (51 \text{ appear}))
= P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))$$
Note the second mistake where we have $+$ instead of $\times$.
 
  • #5
I like Serena said:
It calculates $P(\lnot (52 \text{ appear})) + P(\lnot (51 \text{ appear}))$.
It's a halfway effort to calculate $P(\text{not overbooked})$.
Properly it should be:
$$P(\text{not overbooked}) = P(\lnot (52 \text{ appear}) \land \lnot (51 \text{ appear}))
= P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))$$
Note the second mistake where we have $+$ instead of $\times$.
Does it hold that $P(\lnot (52 \text{ appear}) \land \lnot (51 \text{ appear}))= P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))$ because the events $\lnot (52 \text{ appear})$ and $\lnot (51 \text{ appear})$ are independent? (Wondering)

It holds that $P(\lnot (52 \text{ appear}))=1-P(52 \text{ appear})=1-B(52;0,05;0)=1-0,07=0,93$ and $P(\lnot (51 \text{ appear}))=1-P(51 \text{ appear})=1-B(52;0,05;1)=1-0,19=0,81$.

Therefore, we get $P(\text{not overbooked})=P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))=0,93 \times 0,81=0,7533$, right? (Wondering)
 
  • #6
mathmari said:
Does it hold that $P(\lnot (52 \text{ appear}) \land \lnot (51 \text{ appear}))= P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))$ because the events $\lnot (52 \text{ appear})$ and $\lnot (51 \text{ appear})$ are independent? (Wondering)

It holds that $P(\lnot (52 \text{ appear}))=1-P(52 \text{ appear})=1-B(52;0,05;0)=1-0,07=0,93$ and $P(\lnot (51 \text{ appear}))=1-P(51 \text{ appear})=1-B(52;0,05;1)=1-0,19=0,81$.

Therefore, we get $P(\text{not overbooked})=P(\lnot (52 \text{ appear})) \times P(\lnot (51 \text{ appear}))=0,93 \times 0,81=0,7533$, right? (Wondering)

Ah, we cannot assume they are independent.
So:
$$P(not\ overbooked)=1-P(overbooked)=1-P(52\ appear)-P(51\ appear)$$
 
  • #7
I like Serena said:
Ah, we cannot assume they are independent.
So:
$$P(not\ overbooked)=1-P(overbooked)=1-P(52\ appear)-P(51\ appear)$$

Ah ok! Thank you! (Handshake)
 

1. What is probability overbooking?

Probability overbooking is a strategy commonly used in the airline and hospitality industries to maximize revenue by selling more tickets or reservations than the available seats or rooms. It is based on the principle that not all customers will show up, and those who do not will cancel or reschedule their bookings, allowing the company to accommodate more customers and avoid empty seats or rooms.

2. How is the probability of no-shows calculated for overbooking?

The probability of no-shows is typically calculated by analyzing historical data on customer behavior, such as past booking patterns, cancellations, and late arrivals. This data is used to determine the average percentage of no-shows and adjust the overbooking rate accordingly.

3. What are the risks and benefits of probability overbooking?

The main benefit of probability overbooking is increased revenue for the company. However, it also carries the risk of overbooking too many seats or rooms, resulting in unhappy customers and potential loss of future business. Additionally, if too many customers do not show up, the company may have to incur additional costs to compensate for their overbooking strategy.

4. Are there any regulations or laws regarding probability overbooking?

There are no specific laws or regulations regarding probability overbooking. However, companies must comply with general consumer protection laws and regulations, such as providing compensation or alternative arrangements if customers are denied boarding or accommodation due to overbooking.

5. How can companies minimize the negative impact of probability overbooking?

Companies can minimize the negative impact of probability overbooking by closely monitoring and adjusting their overbooking rates based on real-time data and customer behavior. They can also have contingency plans in place, such as offering incentives for customers to voluntarily give up their seats or rooms, and providing prompt and fair compensation for any inconveniences caused by overbooking.

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