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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

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1 Answer 1

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.

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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

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