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The Law of Large Numbers (LLN) states that as the number of independent trials \(n\) increases, the sample mean \(\overline{X}_n\):
Oscillates further away from the expected value \(\mu\).
Converges toward the theoretical expected value \(\mu\).
Always becomes exactly equal to \(\mu\) for a large enough \(n\).
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