On 18 Jun 2001 01:18:37 -0700, [EMAIL PROTECTED] (Monica De Stefani)
wrote:
> 1) Are there some conditions which I can apply normality to Kendall
> tau?
tau is *lumpy* in its distribution for N less than 10.
And all rank-order statistics are a bit problematic when
you try to use them on rating scales with just a few discrete
scores -- the tied values give you bad scaling intervals,
and the estimate of variance won't be very good,either.
For correlations, your assumption of 'normality' is usually
applied to the values at zero.
> I was wondering if x's observations must be
> independent and y's observations must be independent to apply
> asymptotically normal limiting
> distribution.
> (null hypothesis = x and y are independent).
> Could you tell me something about?
- Independence is needed for just about any tests.
I started to say (as a minor piece of exaggeration) that
independence is needed "absolutely";
but the correct statement, I think, is that independence
is always demanded "relative to the error term."
[ snip, non-linear?]
"Monotonic" is the term.
[ snip, T(z): I don't know what that is.]
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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