Re: Analysing performance data (somewhat OT stat question; sorry)

[Mike Miller]

On Wed, 22 Sep 2004, James Knowles wrote:

> I've been collecting performance data for different software 
> configurations, and examining it in Octave.
>
> It's been about 15 year since college stats class, so I'm rusty. Some 
> data distributions are normal, and a simple t-test works great for 
> testing whether there's a significant difference between configurations. 
> Many are visually "obvious," but some are not. They all need to be 
> documented, however.
>
> Some are heavily skewed, scrunched up near zero. I don't remember what 
> this kind of distribution is called. I do not remember what to use here 
> to test a null-hypothesis of the two data populations being the same. 
> (Yes, inaccurate terminology; sorry.)
>
> Octave has alot built in, and I don't want to just plug data in 
> randomly.


I don't know what your question is.  The chi-square distribution on 1 
degree of freedom has infinite density at zero.  Maybe you're thinking fo 
that one.

Anyway, the "Mann-Whitney U test," also called "Wilcoxon Rank-Sum test" is 
nice for comparing means when the distributional assumptions of the t test 
are not met.  There is not great loss of power when the distributions are 
normal, and there can be very substantial gains in power when the 
distributions are non-normal.

Mike

--
Michael B. Miller, Ph.D.
Assistant Professor
Division of Epidemiology and Community Health
and Institute of Human Genetics
University of Minnesota
http://taxa.epi.umn.edu/~mbmiller/



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