Now, I dunno nuffin' 'bout no Statistics Theory, but I was able to graph this as a branching tree in a way that made sense to me and brought myself to what I thought was a satisfying conclusion.
Typed Response
The probability of the game reaching any particular round is given by PG=1/2n where n is the number of rounds.
Probability of player "B," or the evens player, winning approaches 1/3 by PB=1/22 + 1/24 + 1/26 + 1/28 ...
I determined the variables were dependent: Who wins the round is precisely dependent on the probability for having reached that round. Arguably this is correlation and not strict dependence, however.
This is close, but you've got an off-by-one error where you calculate the probability of making it to the nth round as 1/2^n. Consider that that would imply you have a probability of 1/2 for the game to make it to round 1, or 1/4 to make it to round 2, etc - it should be 1/2^(n-1). Correcting this would give you the correct answers for P(B) and P(C).
As for the dependence question, I'm not sure I followed your arguments there - but saying both are dependent is not correct.
im not sure i understand either. could you tell me what dependence and independence mean in this context? perhaps that is the source of my confusion. i understood it in a naive sense of one variable depending on the other for its outcome, and that whether the evens player wins is simply dependent on the number of the round. B therefore A and C therefore not A seem like tautological and equivalent dependencies(?) if i understand the question, and there is a good chance i do not. Ah, but i reread "at least" now, which changes everything.
Yes, i'm quite certain now: I do not understand.
also, how come i got the right probability for the players' winrate if my calculation of that was based on one over two to the n instead of the n minus one? Why didnt the off by one error carry forward giving the odds player the 1/3 chance and vice versa?
One of A,B or A,C is dependent, as it'd flip the polarity of the remaining games, the other is independent, as it wouldn't. I'm not too worried about which is which, as it's just an off-by-one error. xD
Assuming no,
You'd have to know the distribution of when games were abandoned, I'd think.
Games are always played to completion, though if you wanna make it (barely) more challenging you can add in a 5% chance for both players to get bored and give up on each round (before flipping), leading to a loss. Though it seems unlikely - after flipping a quarter 20 times and getting Tails every time, I'd be inclined to keep flipping if anything.
response
These are correct. It is possible to reason out which of B and C is independent of A without going into the numbers.
I read the other answers in the thread, and I definitely would have gotten this wrong without that. This answer stands a chance at least
Independence
A and C are independent, A and B are not. Since you have a chance to win on turn 4 that you do not have on turn 1, P(A|B) = 1/2 + 1/16 + 1/64... = 7/12 != P(A). Conversely, P(A|C) = 1/4 + 1/16 + 1/64... = 1/3 = P(A)
This is the correct answer, although P(A|B) should actually be 2/3 rather than 7/12 - I think you meant 1/2 + 1/8 + 1/32 + ...?
The reasoning is good, either way. Since past flips won't affect future flips, if the player has made it to turn 5, an odd turn, then their future prospects are no different than they were on turn 1, another odd turn - so A and C are independent. Similarly, A and B are dependent because your chances of winning and losing effectively flip: If you've made it to an even turn, then you now win if it takes an odd number of flips from there to get Heads.
So it should be an almost paradoxical-seeming situation: You win 1/3 games overall, you win 2/3 games that make it to turn 2, you win 1/3 games that make it to turn 3, you win 2/3 games that make it to turn 4, 1/3 that make it to turn 5, etc.
Thanks for the catch! Once I noticed that the probability of winning on the initial flip was the difference between the two, I stopped thinking about the other terms...