Summary of Variance Learning

Before the analysis, we should strictly distinguish whether a concept is defined in terms of probability or statistics . Probability is more abstract than statistics, probability studies the ideal case of an event, but in the real world, this ideal situation is difficult or impossible to achieve, so use statistical samples to estimate the ideal result.

Concept and definition of variance

The difference in probability theory is used to measure the degree of deviation between a random variable and its mathematical expectation (mean).

Variance in Statistics (sample variance) is the average of the sum of squares of the difference between each data and its average.

Set X is a random variable that, if present, is called the variance of X, recorded as D (x) or Var (x).

D (x) is a measure of the degree of dispersion of X-values, which is a yardstick for measuring the degree of dispersion of a value.

Types and calculation of variance

Discrete-Variance:

D (x) =\sum_{i=1}^{n}p_{i}\cdot (X_{I}-\MU) ^{2} utility bill

Summary of Variance Learning