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Vector form of central limit theorem
Vector form of central limit theorem: variance of x mean = variance of x/number of samples. Mathematical expectation of x mean = mathematical expectation of x.

Taking notes is a form of standard orthogonal distribution, and a form that has not been transformed into standard orthogonal distribution is given. Basically the same (x mean -x expectation)/When the difference under the root sign obeys the standard orthogonal normal distribution, the x mean obeys the normal distribution with x expectation, and the variance obeys the variance with x mean.

App application

The central limit theorem is the most important theorem in probability theory, which supports the calculation formulas and related theories of T test and hypothesis test related to confidence interval. Without this theorem, the following deduction formula will not hold. In fact, the above two interpretations of the central limit theorem can play a certain role in determining the index confidence interval of A/B test in different scenarios.