[R] ANOVA-like tests of geometrically-distributed data
rmerkel at venus.it.swin.edu.au
Tue Jul 16 08:04:37 CEST 2002
I have a statistical problem which has given me no end of grief recently,
and am posting here in the hope that somebody can give me a straight
answer. I'm a IT postgrad, not a statistician, so people may have to
speak really slowly and clearly for me to get it :)
I am collecting simulation data, and the results are geometrically
distributed (or approximately so). From what I can gather from my stats
books, provided the sample size is large enough (>30 or so) I can use t
and z-tests to compare means under different experimental conditions as
the CLT says that the sample means will be approximately normally
However, also as I understand it, the ANOVA explicitly assumes that the
population is normally distributed, which is an assumption that in my case
is not satisfied.
I have also been told that something called a "generalized linear model"
can be used to perform ANOVA-like statistics on geometrically-distributed
data, but not how.
There is R documentation on a function "glm" and also "anova.glm" which
discuss stuff that looks vaguely like what I want to do, but I can't
really make sense of it.
Can these functions do what I'm trying to do? If so, what's the
Any help will be *much* appreciated.
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