Odds of Someone Having Same Name and Birthday
According to your purported formula the probabilty of having two people with the same birthday when you only have n 1 person is. Answer 1 of 2.
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Try it yourself here use 30 and 365 and press Go.
. P 1 1 364 365 1 1 364 365 1 365 0. So the probability for 30 people is about 70. What is the probability that her birthday is different from the other two.
Multiply this probability by the world population which well round to 7 billion and you get. I often get mistaken for a 500 foot tall lizard. And the probability for 57 people is 99 almost certain Simulation.
It appears wrong but is in fact true. The birthday paradox is a veridical paradox. In probability theory the birthday problem asks for the probability that in a set of n randomly chosen people at least two will share a birthday.
As mentioned before in a group of 23 people there are 253 comparisons or combinations. Same first and last names would depend on the country and hence the number of people. B Now add a third person.
Ignoring leap years there are 365 days in a year so the probability a given person has the same birthday as you is 1365. The birthday paradox is that counterintuitively the probability of a shared birthday exceeds 50 in a group of only 23 people. Are there people with the same name and birthday.
Since there are 363 days still unused out of 365 we have p 363365 about. If you have a really common name that 1 in 1000 people have then the probability of someone having the same birthday and name as you will be 1365250. Get a large and relevant set of names.
F 1 1 p n 1 44 999 999 999 45 000 000 000 45 000 000 000 000 000 1 3 10 420000 1 100. So you are ascribing a non-zero probability to an impossible event. Same first and last not so much.
Which is approximately equal to 706. While it may seem. We can also simulate this using random numbers.
100 probability of getting at least one pair from USA of same name same date of birth and same gender. Born on the same date in 1948 and such coincidences are surprisingly common. Well building on the Birthday Paradox which shows that if you have 23 people in a room its better than 5050 that two will have the same birthday and for most people at school where the set is restricted to people around your age this normally meant two people with the same birth date day month year on one occasion at school I was in a.
So you might decide that the probability of having the same birthdate year month and day was 13000 and the probability of having the same name was 120000 so the probability of having the same name AND the same birthday would be 13000 times 140000 or 1120000000. 2 Assuming you fixed 1 by multiplying 12. A thousand random trials will be run and the results given.
Of the 620 people with the same name we expect that 620365 or approximately 17 people will have the same name and the same birthday as you. So the probability that someone shares a birthday with someone else is 07063-- it keeps going. If you have a name like Winsemius the odds are much greater against any.
Of course for any one person the odds of someone else having the same name and birth date is small. In a room of 75 theres a 999 chance of at least two people matching. It is however such a rarity that we had trouble finding another couple with the same birthday for us to get their opinion on it.
So the chances are n 36 million. And in a group of 300 people the probability that two share a birth date match is approximately 90. If you want probability you need to divide that by the number of people in the UK.
In a room of just 23 people theres a 50-50 chance of at least two people having the same birthday. 1 There are twelve possible choices you can give to the people with the same name. You stop when you find a proper pair.
Which is kind of a neat result because if you have 30 people in a room you might say oh wow what are the odds that someone has the same birthday as someone else. The probability to get at least one pair is one minus the probability that you dont. The remaining 7-n people can have same name as well and this duplication needs to be subtracted from your counting.
My first name is fairly rare in Canada and combined with my 2 middle names and last name the last name is somewhat common its almost impossile for anyone else to have the same full name location and birthdate. That means 1 minus 029. Unfortunately yes there is flaw.
We can conjecture all sorts of solution methods but Id go empirical on this one. And the probability for 23 people is about 50. You have a database of n name-birthdays all assumed to be equally likely and let us say distinct.
Tally up the frequencies of each three-letter set. If your library serves all of New York City and assuming everyone there has one of these 4025 names then there is a 1 in 4 chance of a single new patron matching your records. Statistically speaking there is a 27 chance of any to people having the same birthday.
So you need to multiply by 12choose 1. Amy Anne Allison counts as AAA Amy. This means that any two people have a 364365 or 99726027 percent chance of not matching birthdays.
This could be from phone listings census records and the like. Multiply those two and you have about 09973 as the probability that any two people have different birthdays or 109973 00027 as the probability that they have the same birthday. Show activity on this post.
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