The End of the Gamblers Who Don’t Understand Probability in Primary School: What is the ‘Monte Carlo Fallacy’?

The subject of probability has been in the curriculum for many years. The subject of probability The fact that it is not understood correctly can cause people to make erroneous inferences from time to time. This situation opens the door to the opportunity to conduct studies for different sciences.

An incident on August 18, 1913, demonstrated this once again after a casino full of gamblers lost millions of dollars due to miscalculation. In psychology, this situation was later The Monte Carlo Fallacy was named.

Gamblers were gambling again that day at the Monte Carlo Casino. One of the most popular games was the game of roulette. In this game, casinos relied on logic called the Law of Large Numbers. (Let me have an article that we will explain this law in detail later.)

When you become a statistician and not a gambler, you can better understand how the casino wins at the game of roulette. Half red and half black on the roulette wheel Total of 36 numbers and green zero is found. The ganyans for black and red are 1 to 2. The value of green color is 36 to 1. When enough hands are played, the dealer wins 1 lira for every 37 lira laid.

The point to be noted here is this: Each time the roulette is turned again, the ball is thrown again. Two roulette games on each other a probabilistic effect not found. The problem with the gamblers was that they didn’t know it.

At the Monte Carlo Casino, something very unusual happened and one after another. those who play black was starting to win. Thereupon, gamblers began to play heavily on the red. If so many blacks overlapped, it should now be red’s turn.

The ball landed on black 27 times in a row that day. The probability of this happening 134 million 217 thousand 728 was. Gamblers had deposited millions of dollars into the casino in one night. Red never came.

Let’s go a step further to understand the error in the logic of the gamblers. let’s ball 26th time it came black. We also know how unlikely the ball is to land 27 times in a row. Isn’t it almost certain that it will come red in this case?

Not.

The probability of getting red and blue colors each time the roulette is rolled is for European roulette. 18/37, for American roulette 18/38(They have a second green slot number 00). The low probability of overlapping does not change the probabilities of the next event. With a red coin on one side and a black side on the other heads or tails If it was thrown and black came 26 times, on the 27th time If we were to use roulette, people’s approach would be different. Since all the trials were at the roulette table, people made the mistake of taking things together.

On the other hand, knowing this phenomenon, Also relying on black on the 28th hand does not explain. The idea that “everyone is in the Monte Carlo Delusion, I’ll go black” only makes sense if the money on the table at the end of the game is to be shared. Because when you think with Bayes Theorem, it is a logical inference. Note that Bayes is not used here, as they are independent events.

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