Hi all, I've issued a pull request (http://github.com/scipy/scipy/pull/227) for a version of scipy/stats/stats.py with the following changes: 1) Adds a method for running a t-test with unequal or unknown population variances. ttest_ind assumes that population variances are equal. 2) Refactored common code in the 4 t-test methods into shared methods. 3) This section of code, which has variations in multiple methods, looks buggy to me: d = np.mean(a,axis) - np.mean(b,axis) svar = ((n1-1)*v1+(n2-1)*v2) / float(df) t = d/np.sqrt(svar*(1.0/n1 + 1.0/n2)) t = np.where((d==0)*(svar==0), 1.0, t) #define t=0/0 = 0, identical means Surely if d=0, regardless of svar, t should be set to 0, not 1. Similarly, if svar = 0 then both variances are zero (assuming that each data set has at least 2 points - perhaps there should be a check for this?). In that case, if d==0 t should be zero. Otherwise, t should be +/-inf. Hence, (svar==0) is redundant. Accordingly, I've changed the lines in all functions to be the equivalent of t = np.where((d==0), 0.0, t) This handles the case where both d and svar are 0. The respective tests have also been changed. If I'm missing something here, please let me know. Thanks, Gavin