| Date: | Fri, 7 Sep 2007 12:02:32 -0700 |
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| Reply-To: | Paige Miller <paige.miller@KODAK.COM> |
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| Sender: | "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU> |
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| From: | Paige Miller <paige.miller@KODAK.COM> |
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| Organization: | http://groups.google.com |
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| Subject: | Re: PROC NPAR1WAY One-Sided Tests |
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| In-Reply-To: | <43C07A163F7E764A8B27F6DAE2B126BF18760DDC@tpwd-mx0.tpwd.state.tx.us> |
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| Content-Type: | text/plain; charset="us-ascii" |
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On Sep 7, 12:11 pm, Warren.Schlec...@TPWD.STATE.TX.US (Warren
Schlechte) wrote:
> In some cases, isn't it the ranks that are important?
>
> In those cases, use PROC Rank to rank the data, then get the sum of the
> ranks to get an idea of which treatment has the higher/lower ranked
> values.
My point is that I shouldn't have to use PROC RANK or any other PROC
to help me understand the output of PROC NPAR1WAY. The output of PROC
NPAR1WAY should be reasonably clear without me needing to comb through
the documentation to see what hypothesis is actually being tested, and
without a need to use PROC SOMETHINGELSE.
--
Paige Miller
paige\dot\miller \at\ kodak\dot\com
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