Hey Folks:

I am trying to define groups within a dataset of water-quality analyses.
 The data need to be analyzed with non-parametric statistics.  However, I
am unsure of my current approach  (See below).

Current Procedure:
Step 1:  Non-metric Multidimensional Scaling  (Euclidean Distance on Scaled
Data)
Step 2:  Hierarchical Cluster Analysis  (Wards Method, Euclidean Distance
of NMDS coordinates)
Step 3: Multi-response Permutation Procedure (Euclidean distance of the
rank-transformed waterquality data, groups defined by Step 2)

Question:
Since NMDS coordinates are non-normal, I am violating the assumptions
behind the Ward's clustering algorithm. However, according to the MRPP
test, the groups are significantly different.  Since MRPP is a
non-parametric test, can I justify using the groups defined through
clustering?

Any suggestions and/or advice would be greatly appreciated.

Thanks!
Nate Jones

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