A New Look at the Central Limit Theorem

Its definition, its many applications, its deep connection with inverse probability, and a glimpse at its history

For all its heft, the Central Limit Theorem has a singularly succinct definition. It says, simply, the following: the standardized sum or mean of a sample of i.i.d. random variables converges in distribution to N(0,1). Built around this central idea is a modest-sized lattice of …

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