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\item If we draw repeated random samples of the same size, n, from some population and measure the mean,$\bar{x}$,we see in each sample, then the collection of these means will pile up around the underlying population mean, $\mu$.  \item The Central Limit Theorem (CLT) states that the distribution of $\bar{x}$ is approximately Normal with mean equal to the population mean, $\mu$, and standard deviation equal to $\frac{\sigma}{\sqrt{n}}$   \[\bar{x} \approx N \left(mean(\bar{x})=$\mu$, SD(\bar{x})=\frac{\sigma}{\sqrt{n}}\right)\] (mean(\bar{x})=$\mu$, SD(\bar{x})=\frac{\sigma}{\sqrt{n}})\]