The Law of Large Numbers is a fundamental concept in probability theory that explains the relationship between theoretical probabilities and observed frequencies. It states that as the number of trials or observations increase, the average outcome of those events will converge to the expected value. In other words, the more times an experiment is repeated, the closer the observed outcomes will be to the predicted probabilities. This principle helps to mitigate the effect of random variations and provides a reliable basis for decision-making in various fields such as finance, statistics, and economics.
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