The Central Limit Theorem (CLT) is a statistical theory states that given a sufficiently large sample size from a population with a finite level of variance, the distribution of the mean samples from the population will be normally distributed.

It is one of the fundamental and key concepts in probability theory.

Basically, it means that no matter what the distribution of the sample is if you sample batches of data from that distribution and take the mean of each batch.

Then the mean values will be normally distributed.

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