The finite variance requirement is a condition in probability theory that stipulates that a random variable has a finite variance, meaning its variance must be a specific numerical value rather than infinite. This requirement is crucial for many statistical theorems and ensures that the average of random samples converges to the expected value as the sample size increases, which is foundational for understanding the behavior of sample means in large samples.
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