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Use Poisson approximations to investigate the following types of coincidences. T

ID: 3306742 • Letter: U

Question

Use Poisson approximations to investigate the following types of coincidences. The usual assumptions of the birthday problem apply, such as that there are 365 days in a year, with all days equally likely (a) How many people are needed to have a 50% chance that at least one of them has the same birthday as you? (b) How many people are needed to have a 50% chance that there are two people who not only were born on the same day, but also were born at the same hour (e.g., two hour) people born between 2 pm and 3 pm are considered to have been born at the same

Explanation / Answer

a. Let I be the first person and a second person comes.

The probability that the second person has a different birthday from me is 364/365.

When a third person comes, the probability that he has a different birthday to the first two is 363/365.

Thus, the probability that there are now no duplicate birthdays is (364/365)*(363/365).

After the fourth one comes in, the probability that he has a different birthday to the first three is 362/365.

The probability that there are now no duplicate birthdays is (364/365)*(363/365)*(362/365). and so on.

It can be seen that the probability that there are no duplicate birthdays falls below 50% when the 23rd person arrives

. Therefore, 23 people are needed to have a 50% chance that at least one of them has the same birthday as I.

b. There are 365 x 24 = 8760 hours in an year. Now same as above, Let a second person comes in.

The probability that the second person has a different birth hour from me is 8759/8760.

When a third person comes, the probability that he has a different birth hour to the first two is 8758/8760

. Thus, the probability that there are now no duplicate birth hours is (8759/8760)*(8758/8760).

After the fourth one comes in, the probability that he has a different birthday to the first three is 8757/8760.

The probability that there are now no duplicate birth hours is (8759/8760)*(8758/8760)*(8757/8760). and so on.

It can be seen that the probability that there are no duplicate birth hour falls below 50% when the 111th person arrives.

Therefore, 111 people are needed to have a 50% chance that at least one of them has the same birth hour as I.

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