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===Measurement of Parameters===
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. Estimators of a set of parameters of a specific distribution are often measured for a population, under the assumption that the population is (at least approximately) distributed according to that specific 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.
===Typesof Parameters Parameters are given names appropriate to their roles, including the following Where a probability distribution has a ___domain over a set of objects that are themselves probability distributions, the term ''[[concentration parameter]]'' is used for quantities that index how variable the outcomes would be.
Quantities such as [[regression coefficient]]s are statistical parameters in the above sense because they index the family of [[conditional probability distribution]]s that describe how the [[dependent and independent variables|dependent variables]] are related to the independent variables.
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