According to the central limit theorem,the standard error for a sample mean becomes smaller as the sample size increases.

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The central limit theorem states that as the sample size increases, the distribution of the 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 means that the standard error, which is the standard deviation of the sampling distribution of the mean, becomes smaller as the sample size increases.

According to the Central Limit Theorem,the Standard Error for a Sample