Definition Central limit theorem

The central limit theorem states that the distribution of central values in a sample approximates a normal distribution with an increasing sample size. It does not matter, however, how the measured values are distributed in the population.

The central limit theorem (CLT) allows us to make statements on the deviations of a central value in a sample without taking into consideration the central values of other samples. The importance of this theorem is, in a nutshell, that it demonstrates that a "large enough" sample sufficiently represents its underlying population as long as the sample is randomly selected.

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