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## Main Question or Discussion Point

Hi, All:

The standard way of approaching the birthday problem, i.e., the problem of

determining the number of people needed to have a certain probability that

two of them have the same birthday, is based on the assumption that birthdays

are uniformly-distributed, i.e., that the probability of someone having a birthday

on a given day is 1/365 for non-leap, or 1/366 for leap.

But there is data to suggest that this assumption does not hold; specifically,

this assumption failed a chi-square at the 95% for expected-actual, for n=480,040

data points.

Does anyone know of a solution that uses a more realistic distribution of birthdates?

The standard way of approaching the birthday problem, i.e., the problem of

determining the number of people needed to have a certain probability that

two of them have the same birthday, is based on the assumption that birthdays

are uniformly-distributed, i.e., that the probability of someone having a birthday

on a given day is 1/365 for non-leap, or 1/366 for leap.

But there is data to suggest that this assumption does not hold; specifically,

this assumption failed a chi-square at the 95% for expected-actual, for n=480,040

data points.

Does anyone know of a solution that uses a more realistic distribution of birthdates?