Most measures of dispersion have the same units as the quantity being measured.

The mean deviation is a different measure of dispersion.

In other words, if the measurements are in metres or seconds, so is the measure of dispersion.

The model considers the thousand futures for which the computed probabilities are the greatest, and makes a measure of dispersion.

Standard deviation: the square root of the variance, and hence another measure of dispersion.

Other measures of dispersion are dimensionless.

One version of this is to use covariance matrices as the multivariate measure of dispersion.

By contrast, the variance is a measure of dispersion of the possible values of the random variable around the expected value.

Gini coefficient has features that make it useful as a measure of dispersion in a population, and inequalities in particular.

Such measures of dispersion include:

"On Measures of Dispersion for a Finite Distribution."

Some measures of dispersion have specialized purposes, among them the Allan variance and the Hadamard variance.

Standard deviation is the frequently used measure of dispersion: it uses squared deviations, and has desirable properties, but is not robust.

CV (coefficient of variation), which is a normalized measure of dispersion of a probability distribution.

Mathematically, the sum of squared deviations is an unscaled, or unadjusted measure of dispersion (also called variability).

Morisita's overlap index, named after Masaaki Morisita, is a statistical measure of dispersion of individuals in a population.

"I-Index, A Measure of Dispersion of Individuals".

Material dispersion is often characterised by the Abbe number, which gives a simple measure of dispersion based on the index of refraction at three specific wavelengths.

The circular standard deviation, which is a useful measure of dispersion for the wrapped Normal distribution and its close relative, the von Mises distribution is given by:

Additional steps may scale the log-ratios by a measure of dispersion such as the standard deviation or median absolute deviation (MAD), possibly grouping spots according to the printing-tip.

L-estimators can also be used as statistics in their own right - for example, the median is a measure of location, and the IQR is a measure of dispersion.

Other than being a component of every statistic that uses all samples, the sample extrema are important parts of the range, a measure of dispersion, and mid-range, a measure of location.

Computationally, this is because in the formulas, the 'μ' terms cancel - adding a constant number to a distribution (and all samples) changes its sample maximum and minimum by the same amount, so it does not change their difference, and likewise for others: these measures of dispersion do not depend on location.