Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It's 100% free, no registration required.

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

I am trying to find a method that will allow me to quantitatively differentiate between 2 distributions. The distributions show a peak where there is positive alignment in a certain direction and have a flat shape when there is no alignment or random alignment. Is there a method for doing this?

Thanks in advance

share|cite|improve this question

The Kolmogorov-Smirnov test may be what you're looking for: it's an omnibus test for difference in two distributions. It has less power than more specific tests (e.g. a $t$-test or permutation test for means) for a given setting, but isn't restricted to just testing one individual aspect of the distribution.

share|cite|improve this answer
Thank you for the reply, however, I need a method where I can compare between 2 groups of frequency distributions. The distributions I obtain are from one sample and I need to compare a few samples from one test group to a few samples of the other. What I am really interested in is the spread of the data and whether it changes from one set to the other. – Jahid Feb 6 '13 at 11:17

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.