In the long run, all casino gambling propositions converge on the normal curve. Slot games are way, way more volatile than any table game, and the same is true there. Remember, each wagering proposition is just a discrete random variable with a payback range between 0 (total loss) and MAX_AWARD, whatever the jackpot is. In most games, there are only two outcomes, so the passline has a distribution of 0 and 2, with slightly more chances of 0. (You can subtract 1 from everything and put it into "table-games" notation.) Any sequence of variables like this eventually starts looking like the normal curve. The variance of the distribution determines how long that takes.
Thanks. Begging your patience, you obviously know the math better than me ...
This makes sense to me based on the distribution of the result, but I'm missing the part about the distribution of the dollar-amount.
This may be a dumb question, but if the payback range cannot be less than zero, how is a normal distribution of the dollar-amount possible? Wouldn't a distribution where the "answer" can't be <0 be applicable?
PS: Please keep it somewhat simple. I have two engineering degrees and am familiar with mathematics, but not so much with the branches of probability and statistical methods. In other words, I know just enough to sound particularly stupid.