[R] detection of outliers

Vito Ricci vito_ricci at yahoo.com
Thu Sep 23 17:19:45 CEST 2004

give a look to:


it's the Grubbs' Test for Outliers. It is based on the
assumption of normality of data.

Other methods of outliers' could:

Run-Sequence Plot
Normal Probability Plot


you wrote:

this is both a statistical and a R question...
what would the best way / test to detect an outlier
value among a series of 10 to 30 values ? for instance
if we have the following dataset:
10,11,12,15,20,22,25,30,500 I d like to have a way to
identify the last data as an outlier (only one
direction). One way would be to calculate abs(mean -
median) and if elevated (to what extent ?) delete the
extreme data then redo.. but is it valid to do so with
so few data ? is the (trimmed mean - mean) more
efficient ? if so, what would be the maximal tolerable
value to use as a threshold ? (I guess it will be
experiment dependent...) tests for skweness will
probably required a larger dataset ? 
any suggestions are very welcome !
thanks for your help
Philippe Guardiola, MD

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