-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
Phguardiol at aol.com
Sent: Thursday, September 23, 2004 7:22 AM
To: r-help at stat.math.ethz.ch
Subject: [R] detection of outliers
Hi,
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