• Variance: the average squared distance between the mean and each data value, $\sigma^2 = \frac{1}{N}\sum_{i=1}^{N}(x_i - \mu)^2$, where $\mu$ is the mean and $N$ is the number of data values. Because the deviations are squared, variance is expressed in squared units. • Standard deviation: the square root of the variance, $\sigma = \sqrt{\sigma^2}$, which returns the measure of spread to the same units as the original data.