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In probability and statistics, variance is a measure of spread among the possible values of a random variable or a list of values.

More information can be found here.

The variance of a set of observed values that is represented by random variable $X$ is its second central moment, the expected value of the squared deviation from the mean $$ \mu = E[X]: \operatorname{Var}(X) = \operatorname{E}\left[(X - \mu)^2 \right]$$

This definition encompasses random variables that are generated by processes that are discrete, continuous, neither, or mixed. The variance can also be thought of as the covariance of a random variable with itself: $$\operatorname{Var}(X) = \operatorname{Cov}(X, X)$$

The variance of a set of observed values that is represented by random variable $X$ is its second central moment, the expected value of the squared deviation from the mean $$ \mu = E[X]: \operatorname{Var}(X) = \operatorname{E}\left[(X - \mu)^2 \right]$$

This definition encompasses random variables that are generated by processes that are discrete, continuous, neither, or mixed. The variance can also be thought of as the covariance of a random variable with itself: $$\operatorname{Var}(X) = \operatorname{Cov}(X, X)$$