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Detecting Outliers in a Two-Way Table: I. Statistical Behavior of Residuals

机译:检测双向表中的异常值:I. 残差的统计行为

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This paper deals with some of the statistical properties of, and methods of analysis for, conventional residuals from additivity in two-way tables. Attention is given to three cases: (i) normal fluctuations superimposed on an additive model; (ii) one outlier added to the condition described in (i); and (iii) two outliers superimposed on the condition in (i). The results are based mainly on empirical sampling and involve average values, correlation properties, the use of theW-statistic (Shapiro and Wilk 24) and of probability plotting methods. Generally speaking, in the null case of no outliers, the residuals do behave much like a normal sample. When one outlier is present, the direct statistical treatment of residuals provides a complete basis for data-analytic judgments, especially through judicious use of probability plots. When two outliers are present, however, the resulting residuals will often not have any noticeable statistical peculiarities.
机译:本文在双向表中讨论了加性常规残差的一些统计特性和分析方法。注意三种情况:(i)叠加在加性模型上的正常波动;(ii) 在(i)中描述的条件下增加了一个异常值;及(iii)叠加在(i)项条件上的两个异常值。结果主要基于经验抽样,涉及平均值、相关属性、W统计量(Shapiro和Wilk [24])的使用和概率绘图方法。一般来说,在没有异常值的零情况下,残差的行为确实与正常样本非常相似。当存在一个异常值时,残差的直接统计处理为数据分析判断提供了完整的基础,特别是通过明智地使用概率图。然而,当存在两个异常值时,得到的残差通常不会有任何明显的统计特性。

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