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When is your birthday? The math behind hash collisions
21–24 of 24 posts
Re: When is your birthday? The math behind hash collisions
#22> What is the probability that you are sharing the same birthday with people around you? > What if I told you that in a room with only 23 people there’s already a 50% chance for two of them to have matching birthdays? I guess it's the subject shift from _you_ to _any two people from a group_ that creates the surprise in the birthday paradox. You definitely need way more than 23 randomly sampled people to get to a hig…
Sup-par phrasing is a subtle advantage of non-AI generated text. In the past, I would be put off by this bad phrasing and the typo ("requier") in the text, but these days, it's a signal that a human took the time to write this, which makes me happy to see. ..or is it "sub-par"?
Thanks for noticing! Exactly that part with "requier" didn't go through grammar check:)
Re: When is your birthday? The math behind hash collisions
#23> What is the probability that you are sharing the same birthday with people around you? > What if I told you that in a room with only 23 people there’s already a 50% chance for two of them to have matching birthdays? I guess it's the subject shift from _you_ to _any two people from a group_ that creates the surprise in the birthday paradox. You definitely need way more than 23 randomly sampled people to get to a hig…
Yeah, they should not have lead with subterfuge. It's still remarkable to many people (myself included) that a pool as small as 23 gives a 50% probability. I think even given that premise, the "50% probability" is still a bit of a rug pull. The casual listener still believes the problem should address the 100% match. A more honest approach is to plainly ask how many people have to be at a party to guarantee there are…
That's a very interesting approach! Such a big difference between 366 people for 100% and only 23 for 50% would have been much more intriguing. Thanks, I'll keep it in mind for the future posts:)
Re: When is your birthday? The math behind hash collisions
#24> What is the probability that you are sharing the same birthday with people around you? > What if I told you that in a room with only 23 people there’s already a 50% chance for two of them to have matching birthdays? I guess it's the subject shift from _you_ to _any two people from a group_ that creates the surprise in the birthday paradox. You definitely need way more than 23 randomly sampled people to get to a hig…
Exactly! The idea was to show how asking the right question can completely change the result, which von Mises himself uses as a core argument in his original article. He tells the story about math bureau showing that they weren't wrong mathematically, they were just answering the wrong question