About: Bootstrap error-adjusted single-sample technique

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In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample. It is based on estimating a probability distribution representing what can be expected from valid samples. This is done use a statistical method called bootstrapping, applied to previous samples that are known to be valid.

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dbo:abstract	In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample. It is based on estimating a probability distribution representing what can be expected from valid samples. This is done use a statistical method called bootstrapping, applied to previous samples that are known to be valid. (en)
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dbp:date	March 2011 (en)
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rdfs:comment	In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample. It is based on estimating a probability distribution representing what can be expected from valid samples. This is done use a statistical method called bootstrapping, applied to previous samples that are known to be valid. (en)
rdfs:label	Bootstrap error-adjusted single-sample technique (en)
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