two sample mean comparison with small and nonnormal data I have three groups. Both have small sample sizes (<10). And we can't check the assumption of normality. I want to compare any two of them.
What to do in this case( unequal small sizes, non-normality)
 A: (This is too long for a comment; if the question is sufficiently clarified - see the comments - it may be edited into a better answer.)
On permutation tests:
The basic idea of a permutation test is that if the null hypothesis is true, the group/category labels are arbitrary and could be reassigned without changing the distribution of the groups. So they are reassigned, in every fashion and a test statistic sensitive to the alternative is calculated; if the null is true, the sample should be a randomly chosen member of that permutation distribution. If the alternative is true, the sample should tend toward being 'extreme' in that distribution (extreme in a sense defined by the ordering resulting from what is most consistent with the alternative).
There's some discussion of permutation tests here, discussion of why they might be used here, discussion of the relationship between permutation tests and randomization tests here, and a little on the choice between permutation tests and t-tests here.
There are examples of different permutation tests done here  and 
here and here and here (see near the end).
A: No matter what you use your power to detect differences will be low. Another possible approach would be using non-parametric tests. If you have three groups you could use Kruskal-Wallis (followed by a multiple comparison procedure if you want to compare them pairwise).
In R you can use kruskal.test for the Kruskall Wallis test and kruskalmc in the pgirmess package for multiple comparisons
