The conversion formula between expectation and variance is: the variance DX is equal to the expectation E(X 2) of the square of the random variable x minus the square of the expectation e (x) of the random variable x.

Expressed by mathematical symbols: dx = e (x 2)-(e (x)) 2. This formula is very important in probability theory and mathematical statistics. It describes the degree of deviation between random variables and their mathematical expectations, that is, variance is a measure of the dispersion degree of random variables.

The greater the variance, the more discrete the random variables, that is, the greater the deviation from mathematical expectations; The smaller the variance, the more concentrated the random variables, that is, the smaller the deviation from the mathematical expectation.