The law of large numbers, part II: Estimating expected values with Monte Carlo analysis

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Little rephrasing from the first part about this important theorem:

The average of a sequence of random variables from the same distribution converges to the expected value of that distribution. — “Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference” by Cameron Davidson-Pilon

In human language, as I had said in the first part, it means, that in short term we can experience wild swings of lucky or unlucky events, but on the longer term,...