The Central Limit Theorem states that when the sample size is increased, the sampling distribution of the sample mean will approach a normal distribution.
This theorem is often used to approximate the population mean. In this example, we will use a simulated data set to demonstrate how the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
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