Copyright © Vassilis Hajivassiliou, LSE 1998-2021
Laws of Large Numbers
Laws of Large Numbers (LLN) state that under particular conditions,
sample moments are consistent estimators of the population moments.
Specifically, the sample mean converges asymptotically to the population
true mean. This can be seen in the following experiments, by observing that
the distribution of the sample mean becomes more and more concentrated
around the true value, the larger the sample size, tending to
collapse (=converge} in Mean Square Error to the true mean.
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