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Fair coins tend to land on the same side they started

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Re: Fair coins tend to land on the same side they started

#121
post #2

About a year ago, we embarked on a quest to answer one of the most intriguing questions: If you flip a fair coin and catch it in hand, what's the probability it lands on the same side it started? Today, we are finally ready to share the results. Thanks to my friends, collaborators, and even strangers from the internet, we collected flippin 350,757 coin flips. We ran several "Coin Tossing Marathons" (e.g., https://you…

Fair coin, unfair flip.

Re: Fair coins tend to land on the same side they started

#122

Earlier quoted context omitted.

I love the math/stats history around gambling-related things, thanks for mentioning this. This method assumes the flipper can't introduce bias. ET Jaynes in his book Probability Theory also mentions that it is easy to learn to flip a fair coin in such a way that the result can be predetermined. I searched a tiny bit for this but couldn't find what he was referring to though.

I’ve heard that, with many hours of practice, dedicated amateurs and many famous magicians are able to do this kind of thing. I wouldn’t call it sleight of hand, but it is similar, although it may fall under that category broadly. I’m not a domain expert but I was taught some simple coin tricks as a child by my artist mom’s artist friend who ran the local frame shop. I never tried or thought to try to favor the coin…

I remember at one point in my childhood learning a trick where it looks like you're flipping the coin, but you're really only causing it to rotate and wobble, meaning it's guaranteed to land on whatever side faced up as you tossed it. I don't remember how I did it though, and a few minutes of trying to recreate the effect has failed.

Re: Fair coins tend to land on the same side they started

#123
post #84

Earlier quoted context omitted.

If anyone wants to test it, someone wrote a short code that simulates doing that 100,000 times: https://www.techiedelight.com/generate-fair-results-biased-c... The coin is biased to come up TAILS 80% of the time, but using Von Neumann's method in the program I got HEADS 50.035%, TAILS 49.965%.

Why would you test it? Probability of two heads: p*p Probability of two tails: (1-p)*(1-p) Probability of head followed by tails: p*(1-p) Probability of tails followed by heads: (1-p)*p It's not difficult to notice that if you remove the first two, the last two form a 50/50 distribution

> Why would you test it

Is this a wrong way to get a right answer?

Re: Fair coins tend to land on the same side they started

#124
post #35

Earlier quoted context omitted.

That's amazing, but I guess it won't help when the person can choose the bias? Because according to the study the person can choose the bias by choosing which side start up. So if the person wants tails based on what you've said, they should always 1. Do the first throw starting tails up. 2. If the first one is tails, then they now want to start second one heads up. 3. If the first one is heads, they will want to try…

> That's amazing, but I guess it won't help when the person can choose the bias? Alice writes on a piece of paper whether to use the result from the first or the second coin, Bob flips the coins however he likes, then once there are two different sides of the coins up, Alice turns over the paper and reveals to Bob which coin contains the result. Though I guess that unnecessarily complicates the procedure – maybe Alic…

There are nice protocols like this that don’t require anyone to visibly flip a coin. See, for example:

https://en.m.wikipedia.org/wiki/Commitment_scheme

Re: Fair coins tend to land on the same side they started

#125

Von Neumann described a very elegant way to get fair results from a biased coin. 1. Flip the coin twice 2. If you get the same result both times, goto 1 3. Now that you have different results for your pair of flips, use the first element of the pair of flips as your result. https://en.wikipedia.org/wiki/Fair_coin#Fair_results_from_a_...

I'm confused, how does this help? If coins are biased to land same-side up, then don't I always have an advantage by guessing whatever side is up before the first throw?

I see what you're getting at, and it's subtle! To simplify the discussion, let's assume we always start out with heads up.

You're right that the first coin is more likely to end up heads. But so is the second coin, and if both occur, that would invalidate the pair of tosses. Now, imagine you guessed tails despite the coin starting on heads. If the first toss lands tails, the second coin is still more likely to land heads, which keeps the pair valid.

In other words, whatever you gain by guessing the side that's up on the first coin, you lose on account of the second coin having that same higher probability of invalidating the pair.

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Using extreme numbers, in case that makes it more clear: imagine a coin that has a 99 % probability of ending up with the same side we start with, and – for simplicity of exposition – we always start with heads facing up before the toss.

If you guess heads, and the first coin lands heads, then there is a 1 % chance that you win, namely that when the second coin lands tails.

If you guess tails, and the first coin lands tails, then there is a 99 % chance that you win, namely that when the second coin lands heads.

The two outcomes of the first coin (99 % and 1 % respectively) perfectly balance out the two valid outcomes of the second coin.

Re: Fair coins tend to land on the same side they started

#126

Von Neumann described a very elegant way to get fair results from a biased coin. 1. Flip the coin twice 2. If you get the same result both times, goto 1 3. Now that you have different results for your pair of flips, use the first element of the pair of flips as your result. https://en.wikipedia.org/wiki/Fair_coin#Fair_results_from_a_...

With all due respect to Von Neumann, intuitively I would change it to use the information in the two coins: one for (X, Y) and another for (Y, X). Not the first.

Re: Fair coins tend to land on the same side they started

#127
post #84

Earlier quoted context omitted.

Why would you test it? Probability of two heads: p*p Probability of two tails: (1-p)*(1-p) Probability of head followed by tails: p*(1-p) Probability of tails followed by heads: (1-p)*p It's not difficult to notice that if you remove the first two, the last two form a 50/50 distribution

Some of us suck at math.

Math is often much more fun and compelling for some people when you both theoretically prove something works and then also convince yourself of the same thing via a numerical experiment. I’m pretty good at math proofs (pure math PhD, wrote some books and papers), but I still love to do numerical experiments. It’s fun, and you also set yourself up to be able to easily ask different questions that may be very hard to answer theoretically.

Re: Fair coins tend to land on the same side they started

#128
post #84

Earlier quoted context omitted.

If anyone wants to test it, someone wrote a short code that simulates doing that 100,000 times: https://www.techiedelight.com/generate-fair-results-biased-c... The coin is biased to come up TAILS 80% of the time, but using Von Neumann's method in the program I got HEADS 50.035%, TAILS 49.965%.

Why would you test it? Probability of two heads: p*p Probability of two tails: (1-p)*(1-p) Probability of head followed by tails: p*(1-p) Probability of tails followed by heads: (1-p)*p It's not difficult to notice that if you remove the first two, the last two form a 50/50 distribution

> Why would you test it?

I recall conversations on Usenet decades ago about the Monty Hall problem[1] in which people gave elementary proofs that probabilities don't change by opening a door. Even from mathematicians and statisticians. People were very insistent that the analytical solution was simple and obvious and that switching doors didn't change anything.

The only thing that changed some people's minds was a program that simulated the Monty Hall problem. This was needed to get people to reconsider their proof when the claim was highly counterintuitive.

[1] https://en.wikipedia.org/wiki/Monty_Hall_problem

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