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

From: Mike Miller
Subject: Re: Analysing performance data (somewhat OT stat question; sorry)
Date: Wed, 22 Sep 2004 23:28:15 -0500 (CDT)

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.


Michael B. Miller, Ph.D.
Assistant Professor
Division of Epidemiology and Community Health
and Institute of Human Genetics
University of Minnesota

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