Generalisation To The Birthday Problem

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Discussion Overview

The discussion revolves around the generalization of the Birthday Problem, specifically focusing on the probability that a certain number of people in a set share the same birthday as a given individual, under the assumption of a uniform distribution of birthdays across 365 days. Participants explore the implications of including or excluding the individual in question from the set and the resulting probability calculations.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant introduces the problem by asking for the probability that exactly m people in a set S share a birthday with person A, given a uniform distribution of birthdays.
  • Another participant notes the distinction between this scenario and the traditional Birthday Problem, emphasizing that the probability should be calculated based on a specific day (A's birthday) rather than any arbitrary day.
  • A participant presents a binomial distribution formula for calculating the probability, but later questions its validity in certain cases, particularly when considering the known presence of A's birthday.
  • One participant suggests that the problem requires a conditional probability approach, given that at least one person (A) has a birthday on the specified day.
  • Another participant acknowledges a misunderstanding regarding the inclusion of A in the set and agrees that the distribution applies differently depending on this inclusion.
  • A participant calculates the probability for the case where no other people in S share A's birthday, suggesting that it aligns with the binomial distribution under certain conditions.

Areas of Agreement / Disagreement

Participants express differing views on how to approach the problem, particularly regarding the inclusion of A in the set and the implications for probability calculations. There is no consensus on the correct method to derive the probability, and the discussion remains unresolved.

Contextual Notes

Participants highlight the subtleties involved in the problem, including the dependency of probabilities on the inclusion of A in the set and the need for conditional probability in certain scenarios. The discussion reflects various assumptions and interpretations that may affect the calculations.

Swn Gwyrdd
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It was my mate's birthday yesterday and he noticed that several other people we know also had their birthdays on the same day. We began discussing the Birthday Problem and attempted solutions for more than 2 people and tried to generalise it, but we couldn't find a satisfactory solution for an arbitrary number of people. So:

For a person A and a set of people S with cardinality n, assuming there are 365 days in a year (i.e ignore leap years) and that birthdays follow a discrete uniform distribution, what is the probability that exactly m people in S have the same birthday as A?

I've read through the ideas discussed here: https://www.physicsforums.com/showthread.php?t=664296 but can't see how to extend it to an arbitrary number of people.

I've also seen similar problems such as section 2.4 in: http://www.math.ucdavis.edu/~tracy/courses/math135A/UsefullCourseMaterial/birthday.pdf
where the probability that at least 1 set of 3 people share a birthday is calculated. Notice that this solution is undefined if |S|>365 so there are several subtleties to the problem.

Any ideas?

Note: It's been the best part of a decade since I've studied probability.
 
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Note that there is an important difference to the 'regular' birthday problem: that assumes we are interested in 2 or more people having their birthday onthe same, arbitrary day of the year.
In this case, you are given a specific day of the year - i.e. A's birthday - and you are wondering about the probability that m other people were also born on that day. If birthdays are distributed uniformly, then this is a binomial distribution, giving
P(n, m) = \binom{n}{m} p^m (1 - p)^{n - m}
where p = \frac{1}{365} is the probability that any of the persons share their birthday with A.
 
CompuChip said:
Note that there is an important difference to the 'regular' birthday problem: that assumes we are interested in 2 or more people having their birthday onthe same, arbitrary day of the year.
In this case, you are given a specific day of the year - i.e. A's birthday - and you are wondering about the probability that m other people were also born on that day. If birthdays are distributed uniformly, then this is a binomial distribution, giving
P(n, m) = \binom{n}{m} p^m (1 - p)^{n - m}
where p = \frac{1}{365} is the probability that any of the persons share their birthday with A.
That is the underlying distribution, but that is not the right answer to the question. A couple of examples to see that this is wrong:
  • Let m=0. Plugging in your equation yields a fairly high probability. For example, its 0.76 for n=100. But since we already know that at least one person has a birthday on the day in question, the probability that zero people have a birthday on that day is identically zero.
  • Suppose the set S contains just one person, A. The probability that exactly one person in the set S has the same birthday as A is identically 1, not 1/365 (which is what your binomial distribution yields).

The fact that we know that at least one person (A) has a birthday on that specific day needs to be taken into account. What's needed to answer the question is a conditional probability, the probability that m people in the set have a birthday on a specific day of the year given that at least one person in the set has a birthday on that day.

I could spell out the answer, but I think it's better to treat this as if it were a homework problem and see if the OP can now arrive at the right result.
 
Ah, I considered the question as A not belonging to the set, i.e. what is the probability that out of n other people, m also have the same birthday.
Thanks for the excellent hints though, I'll let the OP figure them out :)
 
Thanks for the replies. I was originally assuming that A\notinS in which case it does follow CompuChip's distribution. Even if A\inS it follows the distribution with n\rightarrown-1 if A's birthday is independent from the others.

So for the case m=0 this is the probability that exactly no other people in S share A's birthday which is:

P(n, 0) = \binom{n - 1}{0} p^0 (1 - p)^{n - 1 - 0} = (1 - p)^{n-1}

This seems to work to me, so I can't get what you're hinting at with the conditional probability since I can't see any way in which the birthdays are dependent.
 

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