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Issue 19, 2015
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Using the Grubbs and Cochran tests to identify outliers

Abstract

In a previous Technical Brief (TB No. 39) three approaches for tackling suspect results were summarised. Median-based and robust methods respectively ignore and down-weight measurements at the extremes of a data set, while significance tests can be used to decide if suspect measurements can be rejected as outliers. This last approach is perhaps still the most popular one, and is used in several standards, despite possible drawbacks. Here significance testing for identifying outliers is considered in more detail with the aid of some typical examples.

Graphical abstract: Using the Grubbs and Cochran tests to identify outliers

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Article information


Submitted
15 Jun 2015
First published
30 Jul 2015

Anal. Methods, 2015,7, 7948-7950
Article type
AMC Technical Brief

Using the Grubbs and Cochran tests to identify outliers

Analytical Methods Committee, AMCTB No. 69, Anal. Methods, 2015, 7, 7948
DOI: 10.1039/C5AY90053K

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