Mathematical Distribution in Slot Machines

Mathematical Distribution in Slot Machines

In mathematics, distribution is a statistical measure that shows how much the measured data changes from the mean value of the set data. In our case, it is the level of risk. The distribution used for gambling is the degree of deviation from the mathematical expectation of the outcome. dispersion makes the game unpredictable, you either win or lose.

Casinos with distribution exist thanks to dispersion: any result would be computed mathematically. distribution is neither a positive nor a negative factor, it exists in itself as an objective reality. To some extent, it allows the player to win (in a short time) compensating for the neat mathematical expectation. At the same time, it does not allow to create of a working system that guarantees earnings for a long time.

In roulette, when you bet on the dispersion “color” it hardly ever happens. However, in practice, there are 15 flat drops of the same color. Learn

Laws of Big Numbers

If the probability of events is equal, it does not mean that we will get an outcome from now on. Suppose we toss ten coins at the same time as coin heads. It makes sense to expect 50% of the articles. However, the probability of being 60% or above is quite high. This happens thanks to the distribution we talked about earlier.

By throwing a coin ten thousand times, we get a balanced value (50%). The probability of getting 60% or more tails in 10 coins random toss = 0.377. Let’s do the same for 100 coins. The probability of getting 60% of the posts is 0.028 or approximately equal. 1 in 35. If he is tossing 1000 coins, it is impossible to get 60% or more of tails. The probability of this event is equal to 0.000000000136 (less than 1 out of 7 billion). We won’t be able to get 50% of the posts, but the more money we have, the closer to the average value (50%).

This is how the “law of large numbers” works: The accuracy of the expected outcome ratio (according to probability theory) is greater when we have more events. Using this law, you can only accurately predict the outcome of a similar series of events. Although the outcome of each event cannot be predicted, it stabilizes over a long period of time.

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