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Using the Grubbs and Cochran tests to identify outliers

机译:使用Grubbs和Cochran测试确定异常值

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摘要

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.
机译:在先前的技术简介(TB第39号)中,总结了三种解决可疑结果的方法。基于中值的方法和健壮的方法分别忽略了数据集的极端值和权重降低的测量值,而显着性测试可用于确定是否可以将可疑测量值作为异常值拒绝。尽管可能存在缺点,但最后一种方法可能仍然是最受欢迎的方法,并且已在多种标准中使用。在这里,借助一些典型示例,对识别离群值的重要性测试进行了更详细的考虑。

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