Coin toss not random after all
mercurynews.com
mercurynews.com
Here's a blog post that explains this in more detail: http://www.billthelizard.com/2009/09/getting-fair-toss-from-...
You can be sure all future coin tosses I do will use this technique!
http://gamesbyemail.com/News/DiceOMatic
It can generate 1.5 million dice rolls per day.
It's a biased flip.
Your solution does not help with that.
It's still an issue, GP is very right. The problem is that you can get any desired outcome with some probability p: it's effectively a coin that changes bias depending on the flipper's preference.
I'm trying to think of a solution that resolves this... thoughts encouraged. :)
Put the coin in the ref's hands, which are cupped against each other in a closed sphere. The ref shakes his hands to the satisfaction of all (and we assume an honest ref). He then places the coin on his thumb, but uses the opposite hand to cover the placing operation and the final launch configuration.
After the coin is positioned, but before it's uncovered, one of the interested parties calls it. Then the coin is tossed.
Fair, random, and evenly distributed as far as I can tell.
Edit: I think this works as well with two interested parties and an impartial ref, or only two opponents where the non-tosser calls the coin before it's tossed.
If one of the interested parties is also the coin tosser, this could offer an opportunity to game the system, though, so one might want to just use your proposal in all cases to avoid complexity.
Thinking about this a bit more, though, I wonder if this really has the desired effect.
Let's assume for a moment that the act of the ref shaking the coin around in his cupped hands actually generates a random starting position. Ok, so starting position is 50/50 heads/tails, and the caller of the coin doesn't know the starting position.
In that case, the final heads/tails probability then depends on the initial starting position -- to use the bad-case numbers from the article, say the final probability is 60/40, favoring the side that was initially facing up.
So what have we really gained here? All we've done is made sure the initial positioning of the coin is random. The bias in the toss itself is still there, but we're hiding it by making sure the caller doesn't know the initial state of the coin.
If that's the case, then why not:
a) Don't even toss the coin at all. If we're convinced that the act of the ref shaking the coin around in his cupped hands gives a random starting position, then why not use that in place of the coin toss?
... or...
b) Avoid the whole cupped-hands shake thing entirely. Just have the interested party call the toss before the ref places the coin on his thumb. Obviously then you have to have an impartial ref who won't then place the coin on his thumb in a way to benefit one of the interested parties. (You could just specify that the ref is required to reach into his pocket, pull out the coin, and place it on his thumb, all without looking at it at all or feeling its surface sufficiently to figure out which side is which.)
I guess it also depends on what we care about to make this "random." Personally I think it's random enough if the caller simply doesn't know the starting position when calling the coin, assuming the coin tosser doesn't use the call to game the toss.
Heh, or we can just admit that tossing a coin isn't sufficiently random, and use something else... like radioactive isotope decay... or even a PC's PRNG (though that of course opens a big computer security debate).
Assuming the cupped hands shake produces a random starting position, you've evenly distributed the toss bias, so the result of a series of tosses should be evenly distributed.
"If that's the case, then why not: a) Don't even toss the coin at all. If we're convinced that the act of the ref shaking the coin around in his cupped hands gives a random starting position, then why not use that in place of the coin toss?"
That's an excellent simplification, but it just doesn't feel as dramatic and traditional to decide on shaking cupped hands. You need the toss for effect.
Obligatory wikipedia link: http://en.wikipedia.org/wiki/Randomness_extractor#Von_Neuman...
If it was random, the output does not depend on the input (or there is no meaningful input).
But they showed that the output depends on the input. So it's NOT random.
Biased random means the result is not uniform, but it does not depends on the input.
No so here. Here it's not biased - it simply depends on the input.
(Obviously pseudo random number generators depend on the input - but those explicitly are not random, they are simply useful.)
Let's assume we have a function true_random() that returns a true random value between 0 and 1. Now let's define f(x) as:
def f(x):
r = true_random()
if r < 0.5: return r
else: return x
This is called Kolmogorov randomness and has nothing to do with how input effects the output. In this instance, any string generated by a million coin tosses couldn't be reproduced by an algorithm that is smaller than the string, in general. By this metric I'd argue that the process is still random.
Just because the input has an effect on the output, doesn't make the output less random. "F(x) = x + rand()" is still a random function.
When the conditions are controlled then so is the probability. The results of this research should not be surprising despite the tone of the article.
Actually, even if you can have data at atomic level you still have chaos theory and butterfly effect preventing you from making prediction. Then even some small fluctuation born by the Plank's "uncertainty principle" can grow up in time to big enough error.
Or, looked at another way, it's not random at all. It's a very simple function of the coin's initial state and the forces applied to it. If you knew all of those, you would be able to predict the results ahead of time.
[0] http://www.dotmancando.info/index.php?/projects/coin-flipper...
So he emphasises that coin tosses obey the laws of physics and are not random, but we use them anyway because we don't know the facts that we need to know in order to call the toss. He included experimental results of successful cheating, but with a jam jar lid instead of a coin. Clearly we call a coin toss "random" because of the practical difficulties involved in predicting the motion of a disk much smaller than a jam jar lid.
If we view a coin flip as a random variable X that describes the number of revolutions, then X has a value of 0 to infinity.
Before the coin is flipped, lets say H faces up. Then as X marks the number of revolutions, R will describe the result:
X: 0 1 2 3 4 5 6 ..
R: H T H T H T H ..
The way to model this would be to come up with a probability distribution for the number of revolutions. If the distribution is skewed towards few revolutions, (something like a poisson distribution, say) then it's very likely that the outcomes have probabilities ≠50% due to the discretisation.
In practical terms, I guess the person flipping the coin should be required to flip it such that it rotates very fast, which ought to provide a gaussian distribution around a high number of revolutions.
I was especially tickled near the end of the article where they described discussions on changing the overtime rules. When they mentioned the players' reaction, I thought it would turn on something related to winning, and I was surprised to learn that their objection was more playing time and more chance of injury.