In statistics, **dispersion** (also called **variability**, **scatter**, or **spread**) is the extent to which a distribution is stretched or squeezed. Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range.

Dispersion is contrasted with location or central tendency, and together they are the most used properties of distributions.

A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse.

Most measures of dispersion have the same units as the quantity being measured. In other words, if the measurements are in metres or seconds, so is the measure of dispersion. Examples of dispersion measures include:

These are frequently used (together with scale factors) as estimators of scale parameters, in which capacity they are called **estimates of scale.** Robust measures of scale are those unaffected by a small number of outliers, and include the IQR and MAD.

All the above measures of statistical dispersion have the useful property that they are **location-invariant** and linear in scale. This means that if a random variable *X* has a dispersion of *S _{X}* then a linear transformation

Other measures of dispersion are **dimensionless**. In other words, they have no units even if the variable itself has units. These include:

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