The central limit theorem states that when taking samples from a distribution with mean and variance the distribution of the sample tends toward a normal distribution with mean and variance as sample size n increases. In the limit as n tends to infinity the sample mean is exactly normally distributed. For large sample sizes (n>30 or n>50) we often assume that the distribution is normal.

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