Dear Chaosheng Zang

The sampling interval is so wide that the high values could easily be related to "hot 
spots" of 
higher grade contamination, i..e dumping areas for particular kinds of slags, 
mineralized 
waste, etc.  A property map might help.

Have you contoured the data?  If so, the sampling interval is so wide that  real hot 
spots of 
environmental significance might not show 2D distribution on such a wide sampling 
grid, 
however.

Regards

Marcel Vallée, Eng,, Geo.
Geoconseil Marcel Vallée Inc.
706 Routhier Ave
Québec, Québec G1X 3J9
Canada
Tel:    (1) 418 652 3497
Fax:    (1) 418 652 9148
Email:  [EMAIL PROTECTED]

==============================================
13/12/01 08:01:48, Chaosheng Zhang <[EMAIL PROTECTED]> wrote:

>
>  Date:   Thu, 13 Dec 2001 13:01:48 +0000
>
>  From:   Chaosheng Zhang <[EMAIL PROTECTED]>
>  Subject:AI-GEOSTATS: Extreme values?
>  To:     [EMAIL PROTECTED]
>
>
>
>  Dear all,
>
>  My question is: How to deal with the extreme/outlying values in a data set?
>
>  I am dealing with heavy metal concentrations in soils from a mine area. The
>
>  sample number is 223, and the samples are spatially evenly distributed with
>  the sampling interval of 400 metres. There are several samples with
>  extremely high values, which makes me feel uncomfortable. The percentiles of
>  the dataset are listed as follows (in mg/kg):
>
>
>                 Zn    Cu     Pb     Cd    As
>          Min     4     1     25    0.0     2
>           5%    35     6     35    0.1     6
>          10%    40     7     41    0.2     7
>
>          25%    65    13     62    0.3     9
>          50%   122    18    168    0.6    15
>          75%   338    27    821    1.5    28
>          90%   907    56   2799    2.8    58
>
>          95%  1986   116   4490    4.2    80
>          96%  2462   151   4698    4.9    82
>          97%  3493   178   5413    6.2    91
>          98%  4697   207   7609    8.3   111
>
>          99%  6712   247  11750   12.4   184
>          Max 11473  1293  16305   48.5  1060
>  When doing geostatistical and statistical analyses, we need some confidence
>  in dealing with the these very high extreme values which account for less
>
>  than 2% of the total sample number.
>
>  Any suggestions?
>
>  Cheers,
>
>  Chaosheng Zhang
>  ===================================
>  Dr. Chaosheng Zhang
>  Department of Geography
>  National University of Ireland
>  Galway
>  IRELAND
>
>  Tel: +353-91-524411 ext. 2375
>  Fax: +353-91-525700
>  Email: [EMAIL PROTECTED]
>  ===================================




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