Excuse the bad grammar or typo noted below... It's been a "long
morning" already, and it's still not 9 am...
:)
Bill
On Fri, 15 Feb 2002, William B. Ware wrote:
> What are your samples sizes? If there are equal or nearly so, the t-test
*they*
> is robust with regard to unequal variances.
>
> On the other hand, you could just read the part of the output that reports
> results for "equal variances not assumed." You might also consider using
> a nonparametric procedure such as the Wilcoxon Rank Sum Test or the
> equivalent Mann Whitney U Test.
>
> You could also consider resampling or permutation tests...
>
> WBW
>
> __________________________________________________________________________
> William B. Ware, Professor and Chair Educational Psychology,
> CB# 3500 Measurement, and Evaluation
> University of North Carolina PHONE (919)-962-7848
> Chapel Hill, NC 27599-3500 FAX: (919)-962-1533
> http://www.unc.edu/~wbware/ EMAIL: [EMAIL PROTECTED]
> __________________________________________________________________________
> On Thu, 14 Feb 2002, Matthias wrote:
>
> > Hello,
> >
> > would be nice if someone can give me some advice with regard to the
> > following problem:
> >
> > I would like to compare the means of two independent numerical sets of data
> > whether they are significantly different from each other or not. One of the
> > two underlying assumption to calculate the T-Test is not given (Variances
> > are assumed to be NOT equally distributed; but data is normally
> > distributed). What kind of (non?)parametric-test does exist - instead of the
> > T-Test - to calculate possible differences in the two means?
> > I'm using SPSS for further calculations.
> >
> > Thank you for your time and help,
> >
> > Matthias
> >
> >
> >
> >
> >
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