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.

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The central limit theorem implies that the sampling distribution of the sample mean will be approximately normally distributed for large sample sizes, and about 95% of the data falls within two standard deviations (standard errors) from the mean in a normal distribution.

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