In [[statistical inference]], parameters are sometimes taken to be unobservable, and in this case the statistician's task is to estimate or infer what they can about the parameter based on a [[random sample]] of observations taken from the full population. ParametersEstimators of a set of parameters of a specific distribution canare beoften measured for a population, under the assumption that the population is (at least approximately) distributed according to that particularspecific probability distribution. In other situations, parameters may be fixed by the nature of the sampling procedure used or the kind of statistical procedure being carried out (for example, the number of degrees of freedom in a [[Pearson's chi-squared test]]). Even if a family of distributions is not specified, quantities such as the [[mean]] and [[variance]] can generally still be regarded as statistical parameters of the population, and statistical procedures can still attempt to make inferences about such population parameters. Parameters of this type are given names appropriate to their roles, including the following.
:*[[___location parameter]]
:*[[Statistical dispersion|dispersion]] parameter or [[scale parameter]]
