ABSTRACT
Central Limit Theorem “Given a population of values with a finite (non-infinite) variance [σ2], if we take independent samples from the population, all of size N, then the population formed by the averages of these samples will tend to have a Gaussian (normal) distribution regardless of what the distribution is of the original population; the larger N, the greater will be this tendency towards ‘normality’. In simpler words: The frequency distribution of sample averages approaches normality, and the larger the samples, the closer is the approach.” 1
