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My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same daythis problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

UPDATE ON Q1 Specifically I am asking what is the method/logic to calculate problems on such conditional probability?

Say, there are 4 genes discovered so far and 6 bases in total; What are the Chances of 2 or more genes sharing same bases.

Given 4 genes ('ABCD') there are following sets of possibilities: [['AB', 'CD'], ['AC', 'BD'], ['AD', 'BC'], ['BC', 'AD'], ['BD', 'AC'], ['CD', 'AB'], ['ABC'], ['ABD'], ['ACD'], ['BCD'], ['ABCD']]

So what are the chances?

My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

UPDATE ON Q1 Specifically I am asking what is the method/logic to calculate problems on such conditional probability?

Say, there are 4 genes discovered so far and 6 bases in total; What are the Chances of 2 or more genes sharing same bases.

Given 4 genes ('ABCD') there are following sets of possibilities: [['AB', 'CD'], ['AC', 'BD'], ['AD', 'BC'], ['BC', 'AD'], ['BD', 'AC'], ['CD', 'AB'], ['ABC'], ['ABD'], ['ACD'], ['BCD'], ['ABCD']]

So what are the chances?

My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

UPDATE ON Q1 Specifically I am asking what is the method/logic to calculate problems on such conditional probability?

Say, there are 4 genes discovered so far and 6 bases in total; What are the Chances of 2 or more genes sharing same bases.

Given 4 genes ('ABCD') there are following sets of possibilities: [['AB', 'CD'], ['AC', 'BD'], ['AD', 'BC'], ['BC', 'AD'], ['BD', 'AC'], ['CD', 'AB'], ['ABC'], ['ABD'], ['ACD'], ['BCD'], ['ABCD']]

So what are the chances?

UPDATE ON Q1
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My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

UPDATE ON Q1 Specifically I am asking what is the method/logic to calculate problems on such conditional probability?

Say, there are 4 genes discovered so far and 6 bases in total; What are the Chances of 2 or more genes sharing same bases.

Given 4 genes ('ABCD') there are following sets of possibilities: [['AB', 'CD'], ['AC', 'BD'], ['AD', 'BC'], ['BC', 'AD'], ['BD', 'AC'], ['CD', 'AB'], ['ABC'], ['ABD'], ['ACD'], ['BCD'], ['ABCD']]

So what are the chances?

My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

My question is: Find the probability that at least 2 people in a room of 30 share the same birthday.

I looked at this problem - Having birthday at the same day after watching the Birthday Probability video ;

the way to solve this problem is 1 - P(unique birthdays) which is quite straightforward.

But, Q1: how to solve it the other way around? Instead of finding unique birthdays, just find P(Same birthdays). How would that happen?

I thought if everyone from 2 to 30 ppl share 365 bdays and order matters then,

365Pr / 365 where r = 2 to 30

and then summing them up will give the total probability

sum([permutation(365,ppl)/365 for ppl in xrange(2,31)])
Decimal('5.965783049451056333110639647E+73')

Evidently that's not the case. so how to solve #1 ?

Also

Q2: What if there were 1000 people in a room since 365 < 1000, how would that go?

UPDATE

With the Q1, what I mean is the chances 2 people share the same bday and 3 ppl might share some other day, while 4 ppl might not share the same day, 17 ppl might share some other day. For the sake of academic discussion, however complex this might be, I am only interested in knowing how does one solve this, say if we reduce the number of people to 5 just to reduce the complexity, I still would like to know how to approach this problem.

UPDATE ON Q1 Specifically I am asking what is the method/logic to calculate problems on such conditional probability?

Say, there are 4 genes discovered so far and 6 bases in total; What are the Chances of 2 or more genes sharing same bases.

Given 4 genes ('ABCD') there are following sets of possibilities: [['AB', 'CD'], ['AC', 'BD'], ['AD', 'BC'], ['BC', 'AD'], ['BD', 'AC'], ['CD', 'AB'], ['ABC'], ['ABD'], ['ACD'], ['BCD'], ['ABCD']]

So what are the chances?

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