Variance

Variance quantifies spread by averaging squared deviations from the mean, so it is always non-negative. The sample variance is $s^2 = \frac{1}{n-1}\sum (x_i - \bar{x})^2$, where $x_i$ are the values, $\bar{x}$ (x-bar) is the mean, and $n$ is the number of values. For example, data tightly packed around the mean have a small variance. Because the deviations are squared, variance is measured in squared units, and its square root is the standard deviation.