EN ET

Variance


Variance or mean squared deviation is a measure of the variability of a random variable, indicating how much the studied quantity varies. A higher Variance indicates greater differences between the values in the observed data set.

Variance Formula

$$\sigma^{2} = E(X - E(X))^{2}$$

where,

E(X)ā€” the expected value (mean) of the random variable X.

Variance of a finite data set can be expressed by the formula:

$$\sigma^{2} = \frac{1}{n}\sum_{i=1}^{n}(x_{i} - \bar{x})^{2}$$

where,

ā€” the mean of random variables xi.

Sample Variance can be expressed by the formula (Bessel's correction):

$$\sigma^{2} = \frac{1}{n-1}\sum_{i=1}^{n}(x_{i} - \bar{x})^{2}$$


Variance may also be denoted by D(X). Often, especially in English literature, Variance is denoted by V(X) or var(X).

See also:


favorite TOP 7