Estimator

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Estimator

Estimator (/ɛstɪmeɪtər/), in the field of statistics, is a rule for calculating an estimate of a given quantity based on observed data.

Etymology

The term "estimator" was coined in the field of statistics and is derived from the English word "estimate," which means to roughly calculate or judge the value, number, quantity, or extent of something.

Definition

An estimator is a statistic that estimates some fact about the population. You can also think of an estimator as the rule that creates an estimate. For example, the sample mean is an estimator of the population mean.

Types of Estimators

There are several types of estimators, including:

  • Point Estimator: A point estimator is a type of estimator that provides a single "best guess" of the parameter of interest.
  • Interval Estimator: An interval estimator provides a range of plausible values for the parameter of interest.
  • Unbiased Estimator: An unbiased estimator is an estimator whose expected value is equal to the parameter being estimated.
  • Consistent Estimator: A consistent estimator is an estimator that converges in probability to the parameter being estimated as the sample size increases.

Related Terms

  • Bias of an Estimator: The bias of an estimator is the difference between this estimator's expected value and the true value of the parameter being estimated.
  • Variance of an Estimator: The variance of an estimator is a measure of how spread out the values of the estimator are likely to be if the process of estimation is repeated a number of times.
  • Efficiency of an Estimator: The efficiency of an estimator refers to the estimator's variance. An efficient estimator is one that has the smallest variance among all unbiased estimators of the same parameter.
  • Sufficiency of an Estimator: Sufficiency of an estimator refers to the property that no other statistic that can be calculated from the same sample provides any additional information as to the value of the parameter to be estimated.

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