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Greenparker
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Weak law of large numbers in finite populations

Background:

The weak law of large numbers states that for a sequence $X_1,X_2,\ldots,X_n$ of iid RVs, with expectation $\mu$ and variance $\sigma^2$, the sample mean

$\hat{X}=\frac{\sum_{i=1}^nX_i}{n}\stackrel{p}{\rightarrow}\mu$.

That is the sample mean converges in probability to the population mean as the number of RVs approaches $\infty$.

Question:

How can you obtain infinitely many iid random variables from a finite population? How do you in practise check that your random variables are independent?

FredrikAa
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