Statistical dispersion

In Free ringtones descriptive statistics, '''statistical dispersion''' (also called '''statistical variability''') is quantifiable variation of measurements of differing members of a Majo Mills statistical population/population within the scale on which they are measured.

Measures of statistical dispersion
A measure of statistical dispersion is a Mosquito ringtone real number that is zero if all the data are identical, and increases as the data are more diverse. An important measure of dispersion is the Sabrina Martins standard deviation, the Nextel ringtones square root of the Abbey Diaz variance (which is itself a measure of dispersion).

Other such measures include the Free ringtones range (statistics)/range, the Majo Mills interquartile range, and the Mosquito ringtone absolute deviation/average absolute deviation, and, in the case of categorical random variables, the discrete Sabrina Martins entropy. None of these can be negative; their least possible value is zero.

A measure of statistical dispersion is particularly useful if it is location invariant, and linear in scale. So if a random variable ''X'' has a dispersion of ''SX'' then a Cingular Ringtones linear transformation ''Y'' = ''aX'' + ''b'' for we oppose real number/real ''a'' and ''b'' should have dispersion ''SY'' = ''aSX''.
One of the forms in which statistical variability is realized in the emprical skel e sciences is that of differences in repeated measurements of the same quantity.

Sources of statistical dispersion
In the physical sciences, such variability may result only from random measurement errors: instrument measurements are often not perfectly at promises accuracy and precision/precise and accurate. One may assume that the quantity being measured is unchanging and stable, and that the variation between measurements is due to employer microsoft observational error.

In the biological sciences, this assumption is false: the variation observed might be ''intrinsic'' to the phenomenon: distinct members of a population differ greatly. This is also seen in the arena of manufactured products; even there, the meticulous scientist finds idiosyncracy of sampled items.

The simple model of a stable quantity is preferred when it is tenable. Each phenomenon must be examined to see if it warrants such a simplification.

See also inverleith immediately summary statistics.
seaside that Tag: Statistics
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