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In article <1992Aug18.214711.6657@mailhost.ocs.mq.edu.au> wskelly@laurel.ocs.mq.edu.au (William Skelly) writes:
>In article <WVENABLE.92Aug18180002@algona.stats.adelaide.edu.au> wvenable@algona.stats.adelaide.edu.au (Bill Venables) writes:

			...............

>>In my opinion statistical inference is all about reliably capturing
>>information from data (and elsewhere if you are a Bayesian); it's not
>>really about coming up with a number from a data set that you can show will
>>be "close" to an unknown parameter value, in some special sense of "close".

>I am not sure I follow you.  From my applications I only want to test
>some null-hypothesis (perhaps a narrow application...but very useful!).
>Generally I want to know if two samples are from the same population.
>Isn't this just asking whether or not the two sample means are close?

If you want the answer to whether two samples are independent samples
from EXACTLY the same population, I need no data to tell you that the
answer is no.  If you want to know if two samples approximately have
this property, and this is a very important problem, the answer may
very well be yes.  But it is necessary to balance the risks.  

In some cases, a good way to do this may be by looking at the closeness
of the sample means, but in other cases, there may be much better ways.
But how to look at them is much more complicated than you were led to
believe.
-- 
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
Phone: (317)494-6054
hrubin@pop.stat.purdue.edu (Internet, bitnet)  
{purdue,pur-ee}!pop.stat!hrubin(UUCP)