Concerning the birthday problem in probability

In summary, the conversation revolves around determining the probability of two people in a group having the same birthday. The correct approach is to calculate the probability that at least two have the same birthday by subtracting the probability of no two having the same birthday from 1. This is done by considering the birthdays of each person in the group and taking into account the fact that the probabilities are not independent, as shown in the example of 366 people.
  • #1
red65
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The problem is stated like this :
There are k people in a room. Assume each person’s birthday is equally likely to be any of the 365 days of the year (we exclude February 29), and that people’s birthdays are independent (we assume there are no twins in the room). What is the probability that two people in the group
have the same birthday?
say that we have 23 people, my approach is to calculate the number of pairs in the group which is 23 choose 2 then multiply these by the probability that 2 people have the same birthday which is 1/356(because the first pick any day from 365 days then the second has a probability of 1/365 of picking the same day )
why my approach is wrong?
thanks.
 
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  • #2
You are wrong in assuming that the probabilities of the pairs having identical birthdays are independent. Consider an extreme example of 366 people. If the first 365 people all have different birthdays, then all the birthdays are taken and the 366th person MUST have the same birthday as someone.

EDIT: the numbers below were incorrect and have been corrected. (Thanks @mathman )
Take this approach. The probability that at least two have the same birthday is 1-(probability that no two have the same birthday). Now calculate the probability that no two have the same birthday. Start with person 1. He can have any of 365 birthdays. Person 2 can have any of the 364 remaining birthdays. Person 3 can have any of the 363 remaining birthdays. Continue like that and see where it gets you.
 
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  • #3
FactChecker said:
You are wrong in assuming that the probabilities of the pairs having identical birthdays are independent. Consider an extreme example of 366 people. If the first 365 people all have different birthdays, then all the birthdays are taken and the 366th person MUST have the same birthday as someone.

Take this approach. The probability that at least two have the same birthday is 1-(probability that no two have the same birthday). Now calculate the probability that no two have the same birthday. Start with person 1. He can have any of 356 birthdays. Person 2 can have any of the 355 remaining birthdays. Person 3 can have any of the 354 remaining birthdays. Continue like that and see where it gets you.
Typo in numbers.
 
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  • #4
mathman said:
Typo in numbers.
Thanks. I corrected them. Sorry.
 
  • #5
red65 said:
The problem is stated like this :
There are k people in a room. Assume each person’s birthday is equally likely to be any of the 365 days of the year (we exclude February 29), and that people’s birthdays are independent (we assume there are no twins in the room). What is the probability that two people in the group
have the same birthday?
say that we have 23 people, my approach is to calculate the number of pairs in the group which is 23

No, it's 23 * 22 / 2 = 253
The first person gives you 23, the second has to be someone different 22, pair AB is the same as pair BA.
red65 said:
choose 2 then multiply these by the probability that 2 people have the same birthday which is 1/356(because the first pick any day from 365 days then the second has a probability of 1/365 of picking the same day )
Yes for one pair so you have 253 chances, each one offering you 1/365 chance. However, there may be more than one pair who have the same birthday, so you can't just multiply 1/365 by 253. In fact if you do the sums correctly you end up with approximately a 50/50 chance. You can do the calculation by finding out the probability of NOT finding a matching pair. Which is (1-1/365)^253. The probabilty of finding one is then 1 minus that. Which is 0.50047715403658201443106172385727
 
  • #6
##1 - \left(\frac{365 \times 364 \times \dots \times 365 - n + 1}{365^n}\right) > 0.5##

I don't know how to solve this inequality.
 
  • #7
Agent Smith said:
##1 - \left(\frac{365 \times 364 \times \dots \times (365 - n + 1)}{365^n}\right) > 0.5##

I don't know how to solve this inequality.
Use trial and error .
 
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  • #8
SammyS said:
Use trial and error .
Yes, but if the problem is new to you that might be a very difficult way to go. Gracias.
 
  • #9
Agent Smith said:
Yes, but if the problem is new to you that might be a very difficult way to go.
But it is the only way to go. If you are interested in finding numerical answers then you need to become proficient in using suitable numerical tools: for this problem my first choice would be Excel, although Python or Matlab would be alternatives.
 
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  • #10
@pbuk that's a good suggestion. Is the formula correct though?
 
  • #11
Agent Smith said:
@pbuk that's a good suggestion. Is the formula correct though?

You have posted:
##\displaystyle \quad\quad 1 - \left(\frac{365 \times 364 \times \dots \times (365 - n + 1)}{365^n}\right) > 0.5##.

The expression on the left hand side of the inequality gives the probability that two people, from a group of ##n\ ##people, have the same birthday.
 
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  • #12
Just to add to what @SammyS wrote, note
  • Although your expression is correct we usually omit a common factor of 365 from numerator and denominator: ## 1 - \left(\dfrac{364 \times \dots \times (365 - n + 1)}{365^{(n-1)}}\right) ##.
  • This expression ignores that fact that some people are born on 29th February.
  • It also assumes that births are evenly spread throughout the year, which is not correct.
  • This is a well-known problem and more information can easily be found on e.g. Wikipedia or (my "go to" for answers to all sorts of mathematical questions) MathWorld.
 
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  • #13
Capture.PNG


@pbuk a year on Mercury is just 88 days :smile: cogito

Gracias for pointing out the details.
 

FAQ: Concerning the birthday problem in probability

What is the birthday problem in probability?

The birthday problem, also known as the birthday paradox, is a famous problem in probability theory that examines the likelihood that, in a group of people, at least two individuals will share the same birthday. Surprisingly, the probability reaches 50% with just 23 people and approaches 100% with 70 people.

How do you calculate the probability in the birthday problem?

To calculate the probability that at least two people in a group share the same birthday, you can use the complement principle. First, calculate the probability that no one shares a birthday, then subtract this from 1. For a group of n people, the probability that no two people share a birthday is given by the product formula: P(no shared birthday) = 365/365 * 364/365 * 363/365 * ... * (365-n+1)/365. The probability of at least one shared birthday is then 1 - P(no shared birthday).

Why is the result of the birthday problem so counterintuitive?

The result of the birthday problem is counterintuitive because people often underestimate the number of possible pairs of individuals in a group. In a group of 23 people, there are 253 unique pairs (calculated using combinations), which makes the probability of at least one shared birthday much higher than most would initially expect.

Does the birthday problem assume a uniform distribution of birthdays?

Yes, the classic birthday problem assumes a uniform distribution of birthdays, meaning each day of the year is equally likely for a birthday. This simplifies the calculations but doesn't account for real-world variations, such as seasonal birth trends or cultural factors.

Can the birthday problem be applied to other scenarios?

Yes, the principles of the birthday problem can be applied to other scenarios involving shared characteristics or collisions. For example, it can be used in computer science to analyze hash functions and the likelihood of hash collisions, or in cryptography to understand the probability of two different inputs producing the same output.

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