Thank you! That is a good question. The ONE random sample in the text means ONE set of random samples. Then (n) in the equation means the number of observations in a sample.

In practice, we typically only have ONE set of random samples. As n is sufficiently enough. We can use the sample mean to estimate the population mean. CLT goes one step further. It allows us to estimate the sampling distribution of the sample mean based on just ONE set of random samples so that we can quantify the variability of the sample mean If we were to take random samples over and over again. As n increases, the standard error becomes smaller, then the sampling distribution becomes tighter, it means we have a more precious estimate of the population mean.

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Data Science | Machine Learning | Economics Consulting https://www.linkedin.com/in/aaron-zhu-53105765/

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