According to the Central Limit Theorem, for large samples the standard error of the sample mean is the population standard deviation divided by the square root of the sample size.

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Quizplus · Accepted Answer

This statement is true. The Central Limit Theorem states that as the sample size increases, the distribution of sample means approaches a normal distribution with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size. This is why we can use the standard error of the sample mean as an estimate of the standard deviation of the sampling distribution of the mean.

According to the Central Limit Theorem, for Large Samples the Standard