There is more to the issue than just termiology. If your car gets across
town in the snowstorm, then you know that it *can* travel through snow. If
your car doesn't make it, then you know it *doesn't* do well. This test has
a yes or no answer. My point was that normality tests (no matter how you
refer to them) tend to be "one-way"---they can make you fairly confident of
non-normality if you get a "significant" result, but (except with very large
sample size), they shouldn't leave you confident that your data *are*
normal.
Dave Parkhurst
-----Original Message-----
From: Nicholas Barrowman <barrowma@mscs.dal.ca>
To: David F. Parkhurst <parkhurs@indiana.edu>
Date: Friday, February 26, 1999 12:16 PM
Subject: Re: [S] Tests for multivariate NON-normality?
>I think the issue is partly one of terminology.
>I would talk about a test OF multivariate normality (not "for"),
>(and similarly a test OF equality of variances).
>The sense is that you are putting multivariate normality TO THE TEST,
>just as you might put your car to the test in a snow storm.
------------------------
>Nick Barrowman, Ph.D. Student,
>Dalhousie University Department of
>Mathematics, Statistics, & Computing Science
>barrowma@mscs.dal.ca
>http://www.mscs.dal.ca/~barrowma
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