Hi,
Yeah, but where can I read and learn about those?
thanks,
"Glen Barnett" <[EMAIL PROTECTED]> wrote in message
96548m$9ii$[EMAIL PROTECTED]">news:96548m$9ii$[EMAIL PROTECTED]...
>
> Neo Sunrider <[EMAIL PROTECTED]> wrote in message
> 0gmh6.222677$[EMAIL PROTECTED]">news:0gmh6.222677$[EMAIL PROTECTED]...
> > I am just taking an undergraduate introductory stats course but now I
> > am faced with a somewhat difficult problem (at least for me).
> >
> > If I want to test a hypothesis (t-test, z-score etc.) and the underlying
> > distribution will under no circumstances aproach normal... (i.e. the
results
> > of the experiement will always be something like 100*10.5, 40*-5 etc.)
The
> > Central Limit Theorem doesn't help here, or does it?
>
> That depends. Depending on what you're testing, and on sample
> size, it may or may not. But it doesn't matter.
>
> It sounds like you probably have a simple enough situation that
> you can make some appropriate assumptions and derive the distribution
> of a reasonable statistic.
>
> > Can anyone explain, or point me in the right direction - how can I test
in
> > these cases?
>
> Nonparametric methods - especially permutation techniques - would be
> a good place to start looking. Even if you don't go this way it might
> clarify some of your ideas in the specific situation you're dealing with.
>
> Glen
>
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