Generally when tossing a coin $n$ times, the probability of getting heads or tails are both $\frac{1}{2}$ for each toss, so if you were to guess heads for every toss, you should expect to get $\frac{1}{2}$ of the tosses correct.
Now I also understand that for $n$ tosses to consecutively be all heads, the probability would be $(\frac{1}{2})^n$.
With this in mind, if you were trying to maximize the amount of correct guesses for $n$ coin tosses, should you be changing your guess after each successful prediction?
It would seem to me that after you successfully guess the toss, let's say for example your guess was heads, the probability of it being heads again on the next toss is now $(\frac{1}{2})^2$, right? So intuitively it would seem like changing your guess to tails in this case would yield a higher success rate for the next toss and so on.
Does this logic stand? I'm trying to figure out a way to prove mathematically that this would work (or doesn't work) and I'm coming up short. Any help in trying to figure this out would be greatly appreciated.