The central limit theorem states that if the sample size, n, is large enough (n ≥20), the distribution of the sample means is normally distributed regardless of the shape of the population.

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The central limit theorem states that the distribution of the sample means will be approximately normally distributed if the sample size is large enough, typically n ≥ 30, not n ≥ 20, and this holds true regardless of the population's distribution shape.

The Central Limit Theorem States That If the Sample Size