4 ms·
Well, it happened, so... 100%? Since you're looking for a specific birthday which occurs (assuming random distribution of birthdays), 1/1461 of the time. I t
by pfarrell 15y ago
Well, it happened, so... 100%?
Since you're looking for a specific birthday which occurs (assuming random distribution of birthdays), 1/1461 of the time. I think you've got n(1/(1461^y)) where n is number of employees and y is the number of people who could have Feb 29. That should give you the percentage likelihood.
1k employees => .4% chance
10k employees => 4% chance
Unless, they're twins :)
- chimeracoder 15y agoOT here. Didn't know that this had been posted - here's my discussion post: http://news.ycombinator.com/item?id=3649114 http://news.ycombinator.com/item?id=3649114 Neglecting the 100- and 400-year problems with leap years, that seems to be a good frequentist estimate. But if you look at it from a Bayesian perspective the question is how much you're interested in incorporating into the model. And there's quite a lot of (Also, the problem as originally stated in 140 chars isn't really well-defined - though if you want to get cheeky with an answer of 100%, let's think about the probability for an unspecified NYC startup, rather than foursquare!)
- pfarrell 15y agoSince human lifetimes are < 100 years, the 400 year problem doesn't apply to our population (yet). I'm going to presume you're unspecified company is not hiring children 12 and under. What do you think about my solution here, though? Close enough?