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The Law of Large Numbers implies that the probability that the error in the estimate of the mean of a random variable is greater than
The Law of Large Numbers implies that the probability that the error in the estimate of the mean of a random variable is greater than epsilon is
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inversely proportional to its variance
proportional to the size of the sample
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inversely proportional to the square of the error
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