The Central Limit Theorem (CLT)says that as long as the sample size is reasonably large,there is about a 95% chance that the magnitude of the sampling error for the mean will be no more than two standard errors.

Question

Quizplus · Accepted Answer

The statement accurately describes the Central Limit Theorem, which states that for a sufficiently large sample size, the distribution of sample means will approach a normal distribution and the standard error can be calculated as the standard deviation of the population divided by the square root of the sample size. It also suggests that typically the sampling error will fall within two standard errors of the mean, with about a 95% confidence level.

The Central Limit Theorem (CLT)says That as Long as the Sample