Bernoulli's Law of Large Numbers states that as the number of trials in a random experiment increases, the empirical probability of an event will converge to its theoretical probability. This principle emphasizes the idea that with a sufficiently large sample size, the average of the results will be close to the expected value, reflecting stability in randomness.
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