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- Newsgroups: sci.math.stat
- Path: sparky!uunet!munnari.oz.au!metro!extro.ucc.su.OZ.AU!simonb
- From: simonb@extro.ucc.su.OZ.AU (Simon Blomberg)
- Subject: Q:Discriminant Function Analysis in Systat
- Message-ID: <simonb.724475528@extro.ucc.su.OZ.AU>
- Keywords: statistics, discriminant function, multivariate, systat
- Sender: news@ucc.su.OZ.AU
- Nntp-Posting-Host: extro.ucc.su.oz.au
- Organization: Sydney University Computing Service, Sydney, NSW, Australia
- Date: Wed, 16 Dec 1992 03:12:08 GMT
- Lines: 38
-
- This post is on behalf of a friend (Diana Fisher, New South Wales
- National Parks and Wildlife service, Australia).
-
- Q. I am using discriminant function analysis to find out which
- variables are best able to discriminate between 2 animal groups,
- using Systat.
-
- My problem is that not enough information is available on each variable
- describing the animals to give a normal distribution; most are in the
- form:
-
- Dependent variable = 0 (Not having the characteristic)
-
- or = 1 (Having the characteristic)
-
- although some have more classes, e.g. body weight which is in 6 classes.
-
- Does this matter? I have a suspicion that body weight is being chosen by
- the analysis as one of the best discriminators because it is in 6, rather
- than 2, classes, unlike the other variables. Could this be right? Does
- internal rescaling prevent this problem? Cross-tabulations do not show
- a large difference between the weights of the 2 animal groups, and
- changing body weight to 2 classes (Heavy vs. light) reduces the importance
- of body weight as a factor.
-
- Thanks in advance,
-
- Diana.
-
- Please e-mail responses to me. I will post a summary of responses to
- sci.math.stat. Thanks.
-
- Simon.
- --
- Simon Blomberg simonb@extro.ucc.su.OZ.AU
- School of Biol. Sciences, A08
- University of Sydney We demand the right to stop to look even at
- NSW 2006 Australia lizards, who are nobody's property. -JBS Haldane
-