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- Bias_of_an_estimator abstract "In statistics, the bias (or bias function) of an estimator is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. Otherwise the estimator is said to be biased. In statistics, "bias" is an objective statement about a function, and while not a desired property, it is not pejorative, unlike the ordinary English use of the term "bias".Bias can also be measured with respect to the median, rather than the mean (expected value), in which case one distinguishes median-unbiased from the usual mean-unbiasedness property. Bias is related to consistency in that consistent estimators are convergent and asymptotically unbiased (hence converge to the correct value), though individual estimators in a consistent sequence may be biased (so long as the bias converges to zero); see bias versus consistency.All else equal, an unbiased estimator is preferable to a biased estimator, but in practice all else is not equal, and biased estimators are frequently used, generally with small bias. When a biased estimator is used, the bias is also estimated. A biased estimator may be used for various reasons: because an unbiased estimator does not exist without further assumptions about a population or is difficult to compute (as in unbiased estimation of standard deviation); because an estimator is median-unbiased but not mean-unbiased (or the reverse); because a biased estimator reduces some loss function (particularly mean squared error) compared with unbiased estimators (notably in shrinkage estimators); or because in some cases being unbiased is too strong a condition, and the only unbiased estimators are not useful. Further, mean-unbiasedness is not preserved under non-linear transformations, though median-unbiasedness is (see effect of transformations); for example, the sample variance is an unbiased estimator for the population variance, but its square root, the sample standard deviation, is a biased estimator for the population standard deviation. These are all illustrated below.".
- Bias_of_an_estimator wikiPageExternalLink georgewbrown.htm.
- Bias_of_an_estimator wikiPageID "8450479".
- Bias_of_an_estimator wikiPageRevisionID "604020608".
- Bias_of_an_estimator hasPhotoCollection Bias_of_an_estimator.
- Bias_of_an_estimator id "p/u095070".
- Bias_of_an_estimator title "Unbiased estimator".
- Bias_of_an_estimator subject Category:Bias.
- Bias_of_an_estimator subject Category:Point_estimation_performance.
- Bias_of_an_estimator subject Category:Statistical_theory.
- Bias_of_an_estimator comment "In statistics, the bias (or bias function) of an estimator is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. Otherwise the estimator is said to be biased.".
- Bias_of_an_estimator label "Biais (statistique)".
- Bias_of_an_estimator label "Bias of an estimator".
- Bias_of_an_estimator label "Erwartungstreue".
- Bias_of_an_estimator label "Несмещённая оценка".
- Bias_of_an_estimator sameAs Erwartungstreue.
- Bias_of_an_estimator sameAs Alboragabetasun.
- Bias_of_an_estimator sameAs Biais_(statistique).
- Bias_of_an_estimator sameAs m.0273vcc.
- Bias_of_an_estimator sameAs Q15222032.
- Bias_of_an_estimator sameAs Q15222032.
- Bias_of_an_estimator wasDerivedFrom Bias_of_an_estimator?oldid=604020608.
- Bias_of_an_estimator isPrimaryTopicOf Bias_of_an_estimator.