What are your samples sizes? If there are equal or nearly so, the t-test 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 > > > > > > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ > ================================================================= > ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
