# Is having too high variance a problem when doing t-test

I am comparing scores of two student groups using t-test (in scikit-learn). Each group has different number of students. Since there are considerable numbers of 0 scores in my data, the standard deviation gets even higher than the mean for the groups. So, I wonder, in this case, if it is still acceptable to keep the 0 scores? I appreciate any information!

• What do the scores mean? Do students actually get scores of 0? The issue for the t test is what the two distributions look like. It doesn't make sense to drop 0 scores if they are real. The t test can be used with unequal sample sizes. It is usually assumed that the two variances are equal when applying the t test for comparing two means. But even in the cases where the two variances are obviously different the Welch test which approximates a t distribution under the null hypothesis can be applied. If the distributions differ greatly from the normal Wilcoxon's rank sum test can be used. – Michael R. Chernick Jan 11 '17 at 18:50
• Thanks for the detailed reply. I wish you can post this as answer! So, if scores of 0 are meaningful in my data, then I should keep them, and high variance does not violate anything as far as I understand. – renakre Jan 11 '17 at 18:55
• @renake I have put the answer part of my comment into a answer as you requested. – Michael R. Chernick Jan 11 '17 at 20:52
• "Having a lot of 0 scores" could be a serious problem if you want the t-statistic to have a t-distribution (i.e. if you want p-values calculated as if you had normally distributed populations to tell you anything) – Glen_b Jan 12 '17 at 0:30