Editing Sampling distribution (section)

{{Short description|Probability distribution of the possible sample outcomes}}
{{Use dmy dates|date=September 2015}}
In [[statistics]], a '''sampling distribution''' or '''finite-sample distribution''' is the [[probability distribution]] of a given [[random sample|random-sample]]-based [[statistic]]. For an arbitrarily large number of samples where each sample, involving multiple observations (data points), is separately used to compute one value of a statistic (for example, the [[sample mean]] or sample [[variance]]) per sample, the sampling distribution is the probability distribution of the values that the statistic takes on. In many contexts, only one sample (i.e., a set of observations) is observed, but the sampling distribution can be found theoretically.

Sampling distributions are important in statistics because they provide a major simplification en route to [[statistical inference]]. More specifically, they allow analytical considerations to be based on the probability distribution of a statistic, rather than on the [[joint probability distribution]] of all the individual sample values.