In article <048a01bfa483$85f46280$[EMAIL PROTECTED]>,
Robert Dawson <[EMAIL PROTECTED]> wrote:
>Michael Granaas wrote (in part):
>> The problem is that interval estimation and null hypothesis testing are
>> seen as distinct species. An interval that includes zero leads to the
>> same logical problems as failure to reject a false null.
Interval estimation at a fixed coverage probability also
does not meet any decision concept; at best, it can be
considered a descriptive statistic. If there is enough
data, and there is no real null, one can use a flat prior,
and act as if the posterior distribution of the parameter
is essentially the normalized likelihood function.
But interval estimation should take into account the size
of the interval. The easiest from a computational standpoint
happens to be linear in this; the action to be taken becomes
quite simple.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
