The so-called sampling distribution refers to the distribution of sample statistics. The distribution formed by the mean of all samples is the sampling distribution of the mean of samples. The shape of sampling distribution of sample mean is related to the distribution of original population. If the original population is normal, then the sample mean obeys the normal distribution regardless of the sample size. The mathematical expectation of its distribution is the population mean, and the variance is 1/n of population variance, that is. If the distribution of the original population is abnormal, it depends on the sample size. When n is a large sample (n≥30), according to the statistical center limit theorem, when the sample size n increases, whether the original population obeys the normal distribution or not, the sampling distribution of the sample mean will tend to obey the normal distribution, and the mathematical expectation of its distribution is the population variance of the population mean with the difference of1/n.