11.10 Grubbs Filter

Name

Grubbs Filter -- Attribute that removes outliers from normally distributed data.

Description

Grubbs' test , (also known as the maximum normed residual test), is a statistical test used to detect outliers in a univariate data set assumed to come from a normally distributed population. It is based on the assumption of normality. That is, one should first verify that the data can be reasonably approximated by a normal distribution before applying. The test detects one outlier at a time. This outlier is expunged from the dataset and the test is iterated until no outliers are detected.

Please note: Multiple iterations change the probabilities of detection, and the test should not be used for sample sizes of six or less since it frequently tags most of the points as outliers.

For a full definition, including formulas, please see the Wikipedia entry.

Input Parameters