Hi

James M. Clark
Professor of Psychology
204-786-9757
204-774-4134 Fax
[email protected]

>>> Michael Palij <[email protected]> 21-Apr-12 4:36 PM >>>
On Sat, 21 Apr 2012 08:01:57 -0700, Jim Clark wrote:
[snip]
>What I do know is that if you select a sample of N observations with mean M and
>standard deviation S out of a population with mean MU and standard deviation
>SIGMA, then:
>
>1.  M will fall within MU +/- z(alpha/2)*SIGMA/sqrt(N) with probability = 1 -
>alpha (hypothesis testing), and

I believe this may be Fisher's position with respect to a one sample test.

>2.  Equivalently, MU will fall within M +/- z(alpha/2)*SIGMA/sqrt(N) with
>probability = 1 - alpha (confidence intervals).

If you have only one CI, your second point is wrong -- this is what Neyman
was emphasizing when he said that for a given CI, it either contained the
population parameter (Prob= 1.00) or it didn't (Prob= 0.00).

JC:

Sorry to disagree, but if 1 is true, 2 is also true.  That is, if M is expected 
to fall within a certain distance of MU with a certain probability, then MU is 
expected to fall within that same distance of M with the same probability.  In 
the latter case, it is the CI that varies from sample to sample with 1-alpha of 
the CIs containing MU, which is staying in position.  

Just as you only have one CI in 2, you only have one M in 1, so it is not 
obvious to me why CIs are prevented from being conceptualized as selected from 
a hypothetical sampling distribution (according to Neyman given Michael's 
summary) while Ms are not so constrained.  To turn the issue around a bit, 
given the way I have phrased #1 (Hypothesis Testing), it is also true that for 
a given sample M, it will either be within a certain distance of MU or not.  
But so what?  We still don't say that p of being in the rejection region is 0 
or 1 based on the outcome for this one trial out of a hypothetical sampling 
distribution.

Perhaps I'm too concrete a thinker, but if I randomly sample 100,000 times from 
a population and calculate the ps as described above, then both 1 and 2 MUST 
both hold true.  It is simply impossible for them not to.  Specifically, with 
respect to 2 and using z = 1.96 and sigma, then 95% of the CIs will contain MU, 
which means that MU falls within my CI 95% of the time.

Take care
Jim



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