In statistics, 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 ordinary English, the term bias is pejorative. In statistics, there are problems for which it may be good to use an estimator with a small bias.

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  • In statistics, 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 ordinary English, the term bias is pejorative. In statistics, there are problems for which it may be good to use an estimator with a small bias. In some cases, an estimator with a small bias may have lesser mean squared error or be median-unbiased (rather than mean-unbiased, the standard unbiasedness property). The property of median-unbiasedness is invariant under transformations while the property of mean-unbiasedness may be lost under nonlinear transformations.
  • Несмещённая оце́нка в математической статистике — это точечная оценка, математическое ожидание которой равно оцениваемому параметру.
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  • Bias (disambiguation)
  • bias of statistical estimators
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  • In statistics, 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 ordinary English, the term bias is pejorative. In statistics, there are problems for which it may be good to use an estimator with a small bias.
  • Несмещённая оце́нка в математической статистике — это точечная оценка, математическое ожидание которой равно оцениваемому параметру.
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  • Bias of an estimator
  • Несмещённая оценка
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