Outlier Correction Analysis Object (Statistics Option)

09.03.2021

You can use this analysis object to remove outliers from a sample. The sample must originate from a normally distributed population.

The analysis object offers you two different tests:

Description

Procedure

David-Hartley-Pearson Test

The test checks whether the highest or lowest value in the sample, depending on which value is furthest from the mean value, is an outlier or not.

Grubbs-Beck Test

The test checks whether the highest and/or lowest value in the sample is an outlier or not.

If outliers are found, these are made void in the result and the test is repeated until no further outliers are found.

References

Hartung, Joachim (1993). Statistik (Statistics), 9th Edition. Oldenbourg Verlag GmbH, Munich. ISBN 3-486-22055-1. Page 344.

Grubbs, Frank E. (1972). Extension of Sample Size and Percentage Points for Significance Tests of Outlying Observations. Technometrics, Vol. 14, No. 4, NOVEMBER 1972, pp. 847-854.

FPScript Functions Used

DavidHartleyPearsonTest

GrubbsBeckTest

See Also

Statistics Option

Analysis Objects

 

Share article or send as email:

You might be interested in these articles