The original question said "to compare distributions to sets of data"
so I believe the discussion concerns the "Goodness of Fit" tests.
The power should be directly related to the sample size vs. test method
used. I plan to run some tests to investigate this.
In article <[EMAIL PROTECTED]>,
[EMAIL PROTECTED] wrote:
> On Tue, 04 Apr 2000 17:41:27 GMT, Madewell <[EMAIL PROTECTED]>
> wrote:
>
> > Let me ask you guys this. If you calculated the power for
> > the Chi-Squared test using both a small and then a large numbers and
did
> > the same for the KS test what would you find?
> >
>
> Which chisquared test? I keep reminding myself that there are an
> awful lot of tests that are ideal, or close to it, that just happen to
> test *different hypotheses* - and it is rather nonsensical to compare
> tests without having that in mind.
>
> The best power the KS is likeliest to appear (though it might be
> elsewhere) at the median split. If you figure beforehand on a median
> split, you could test that single, special hypothesis with a
> chisquared, and that chisquared would outperform the KS for that
> alternative.
>
> Of course, using a bunch of not-ordered categories will give you a
> weak test on ORDERED values, compared to any test that does treat them
> as Ordered, whether you collapse them into categories or not.
>
> --
> Rich Ulrich, [EMAIL PROTECTED]
> http://www.pitt.edu/~wpilib/index.html
>
--
Madewell
Interests: Engineering Management, Reliability Engineering,
Failure Analysis, Statistical Methods.
Sent via Deja.com http://www.deja.com/
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