The formula of variance is S2 = {(x1-m) 2+(x2-m) 2+(x3-m) 2+…+(xn-m) 2}/n, where m is the average value of data, n is the number of data and S2 is the variance. Text is expressed as an average, and its variance is equal to the sum of squares of the deviation of each data from its arithmetic average. Among them, they are discrete and continuous calculation formulas respectively. It is called standard deviation or mean square deviation, and variance describes the degree of fluctuation.

Variance is a measure of dispersion when probability theory and statistical variance measure random variables or a set of data. Variance describes the deviation between random variables and mathematical expectations.

When the data distribution is scattered, the sum of squares of the difference between each data and the average value is large, and the variance is large; When the data distribution is concentrated, the sum of squares of the differences between each data and the average value is very small. Therefore, the greater the variance, the greater the data fluctuation; The smaller the variance, the smaller the data fluctuation.