Thanks.  What's a reasonable multiple to use?


On Mon, Jan 9, 2012 at 7:41 PM, Brian Schott <[email protected]> wrote:

> John Tukey has studied outliers extensively in his interactive data
> analysis. He computes a box plot by measuring the IQR, that's
> interquartile range, of the data set. He adds and subtracts a multiple
> of the IQR to the upper and lower quartiles of the box in the boxplot.
> Data values outside the "hinges" (in Tukey speak) are outliers.
>
> The code below is from Donald R. McNeil's IDA, A Practical Primer.
>
> http://www.pixentral.com/show.php?picture=1Fnz2FOWX9nuYzndC9GbDbi2z1yz50
>
>
> ---
> (B=)
>
> On Jan 9, 2012, at 7:49 PM, Roger Hui <[email protected]> wrote:
>
> > I wonder if there are well-known techniques in statistics for dealing
> with
> > the following problem.
> >
> >      t
> > 11 10 10 10 10 11 10 10 10 10 9 11 10 11 10 10 11 10 11 10 11 10 10
> >      11 10 11 10 10 10 11 10 74 11 11 14 11 11 10 12 11 15 14 12 11
> >      11 11 11 11 10 12 11 11 11 10 11 11 11 10 11 11 10 11 161241 49
> >      32 12 11 11 12 10 11 10 12 11 12 11 11 12 11 11 12 11 11 11 12
> >      11 11 12 11 11 11 11 11 11 11 10 11 11 12 12
> >
> > t is a set of samples from a noisy source which is supposed to give the
> > same integer answer.  Obviously, 161241 is an "outlier", and it is likely
> > that 74, 49, or even 32 are outliers too.  Are there standard techniques
> > for discarding outliers to clean up the data, before the application of
> > statistical tests such as the means test or large sample test?
>
>
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