In article <[EMAIL PROTECTED]>,
les ander <[EMAIL PROTECTED]> wrote:

> Yes, there is an upper bound to the data and i should have said
> binomial.  However, for the null hypothesis i am not sure if p=0.5
> is appropriate since i want to actually test for hypothesis that
> there is no dependence on the input variable.  i am measuring some
> discrete characteristic of a some object as a function of the
> discrete length (i.e. 1 unit, 2units etc) and the when i plot this
> measure (which is length normalized measure) i see that there is
> some correlation i.e. it looks like a binomial distribution with p =
> 0.1 . I had expected to see that this measure should not vary with
> length . Does'nt this mean that I should calculate some measure of
> nonuniformity? (i.e. compare it Uniform(0,Length) ) ?

It seems that what you actually have is a regression problem.  It
probably has nothing to do with testing for "uniformity".  Instead,
you perhaps need to test whether a regression coefficient is zero or
not.  You haven't said enough to tell what's really going on, though.

I suggest you find someone to talk about your problem with in person.

   Radford Neal
.
.
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