say:
we have two games
one game has SD = X and is played f% of the time
the other game has SD = Y and is played z% of the time
mathematically what is the proper way to calculate the 'combined' standard deviation?
I would start with this thread, which seems like it was active only a couple months ago, but is actually two years old, WTF?
Yes. First of all, there's a question of how you're calculating SD to begin with. If you're playing on a computer which is tracking your results by hand, that's probably okay. SD(total) = sqrt(SD(1)^2 + SD(2)^2 + SD(3)^2).
But more often, SD is calculated from session wins, which means you calculate SD(total) = sqrt((ActualWin(1)-ExpectedWin(1))^2 + (ActualWin(2)-ExpectedWin(2))^2 + ... (ActualWin(n)-ExpectedWin(n))^2).
Assuming f and z are fractions rather than percents for simplicity.
Variance=(f*X^2+z*Y^2)
Sandard_Deviation=SquareRoot(Variance)
ok, thank you ICNT.
so digressing a bit......
say you have in the case of blackjack
SD = Z for a hand of blackjack
so to get the standard deviation for N hands would it be:
Z*SQRT(N) ?
yep that is why accumulated expectations overcome accumulated standard deviations as the number of hands increases, because the former (expectation) is proportional to the number of hands, while SD is proportional to the square root of the number of hands