I am back because of an interesting thing called Birthday Paradox

Let's see how many of us share a common birthday.

I will edit this post to add to the list, just post your replies in this format

Code:
```1) Jackie Chan April 7
2) Prelude Nov 11
3) Neo1 October 11
4) brewbuck February 7
5) ahluka June 7
6) ping December 15
7) anon October 25
8) indigo0086 June 13
9) Mario F. August 23
10) BMJ May 29
11) maxorator March 25
12) SlyMaelstrom August 10
13) abh!shek January 10
14) P4R4N01D 28 February
15) QuantumPete 11th August```

2. Cboard has a calendar, you know. It's probably going to give you a better sample than a few people on a single thread.

Prelude Nov 11

3. Neo1 October 11

4. brewbuck February 7

5. ahluka June 7

6. ping December 15

7. anon October 25

We could probably get 365 replies before we find 2 people that have birthday on the same day (it would be great to disprove the paradox )

8. June 13....

I'm Serial.

9. Alas. The theory falls.

August 23.

10. Well, it doesn't help if a person with a matching birthday deliberately doesn't post theirs

11. BMJ May 29

12. Originally Posted by brewbuck
Well, it doesn't help if a person with a matching birthday deliberately doesn't post theirs
That's the beauty of these probability theories; they explain nothing because they can't be disproven. Only proven. That is, they are true because that's just the nature of probabilities.

Or better yet, for every set of results that disprove the theory, one can always argue a bigger set can prove it.

I'm not sure why we should waste time on it
The exact same theory can immediately be applied to people's height, weight, cars with the same two initial letters in their license plates, poking my nose at the same time as someone else...

13. March 25

14. That's the beauty of these probability theories; they explain nothing because they can't be disproven. Only proven. That is, they are true because that's just the nature of probabilities.
I wouldn't say that the likelihood of an event occuring (even if in real world demonstration it is very unlikely because only a subset of humanity will ever produce an evenly distributed sample) makes the statement any less of a fact. You could simulate a number of assumptions by computer:

Code:
```// Nobody in the sample was born on February 29
// Everyone's birthdays in the sample are evenly distributed

{
return n == 1 ? 1.0 : (365.0 - (n - 1)) / 365.0 * bd_paradox(n - 1);
}

#include <iostream>
#include <ostream>
#include <iomanip>
int main ()
{
for ( int n = 1; n <= 365; n++ ) {
std::cout << n << ": " << std::scientific << 1.0 - bd_paradox(n) << '\n';
}
return 0;
}

1: 0.000000e+000
2: 2.739726e-003
3: 8.204166e-003
4: 1.635591e-002
5: 2.713557e-002
6: 4.046248e-002
7: 5.623570e-002
8: 7.433529e-002
9: 9.462383e-002
10: 1.169482e-001
11: 1.411414e-001
12: 1.670248e-001
13: 1.944103e-001
14: 2.231025e-001
15: 2.529013e-001
16: 2.836040e-001
17: 3.150077e-001
18: 3.469114e-001
19: 3.791185e-001
20: 4.114384e-001
21: 4.436883e-001
22: 4.756953e-001
23: 5.072972e-001
24: 5.383443e-001

// and so on ...```
But it certainly has applications. The birthday paradox shows that even if the number of bins is much greater than the number of items, the probability that two items will randomly be put into the same bin is still very high. The lesson to be learned in relation to computer science is that efficient handling of the bins containing lots of items is always necessary.

15. Hmm... interesting point.