The Law of Large Numbers is a fundamental theorem in probability and statistics that describes the result of performing the same experiment a large number of times. It states that as the number of trials of a random experiment increases, the sample mean (or average) of the results will tend to converge to the expected value (the theoretical mean) of the underlying probability distribution.
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