2 ms·
This can also be theoretically proven: 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 infin
by rjprins 17y ago
This can also be theoretically proven:
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 ..
As you can see for any value of X, the number of times H was up is always equal or once more then T. This shows a clear bias for the side facing up.
- pmjordan 17y agoUhhh, careful with "once more" in the context of infinity. 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.