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submitted 11 months ago* (last edited 11 months ago) by PetDinosaurs@lemmy.world to c/technology@lemmy.world

The paper shows some significant evidence that human coin flips are not as fair as I would have expected (plus probably a bunch of people would agree with me). There's always some probability that this happened by chance, but this is pretty low.

Of course, we should be able to build a really accurate coin flipping machine, but I never would have expected such a bias for human flippers.

This is why science is awesome and challenging your ideas is important.

Edit: hopefully this is not too wrong a place, but Lemmy is small, and I didn't know where else I could share such an exciting finding.

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[-] ericbomb@lemmy.world 8 points 11 months ago

Now I wanna know if I can get better at landing on the same side on purpose...

[-] PetDinosaurs@lemmy.world 8 points 11 months ago* (last edited 11 months ago)

Yeah... I had that thought for a second. Then I geeked out on the math and came to the same conclusion I had before.

Just as I won't learn to play poker or count cards, I'm not learning and practicing this.

I've got other things to do with my limited life.

[-] nous@programming.dev 1 points 11 months ago

I suspect you can, if there is a bias when no effort is applied I suspect you can train to increase it. I can think of two main factors at play - how fast the coin is rotating and how long it remains in the air. Both of which are under your control and I suspect you can train to become more reliable for though it might take a lot of effort. Or you can just learn to do this in 10 mins. Who is going to know the difference? It is cheating either way.

[-] SayJess@lemmy.blahaj.zone 2 points 11 months ago

Great minds think alike! I just referenced this video in another thread on this post, without having read your comment first!

[-] PipedLinkBot@feddit.rocks 1 points 11 months ago

Here is an alternative Piped link(s):

Or you can just learn to do this in 10 mins

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this post was submitted on 10 Oct 2023
145 points (95.0% liked)

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