i was not really looking for the "crafty" way but ... a simple and direct
interpretation (if one IS possible)
say ... we have some concern about whether the average IQ is still 100 in
the general population ... as test publishers say (of course, herman rubin
would say that we know that this null is NOT really (exactly) true ... but,
let's put this aside for the moment)
now, we take (if this is really possible) a random sample of 100 ... do a
simple t test with the null being 100 and ... the p value comes out to be
.08 ... TEST A
or, this test turned up a p value of .02 ... TEST B
or, this test turned up a p value of .008 ... TEST C
assume for a moment that we did things correctly in terms of sampling, run
the right test, assumptions met, etc.
are we able to accurately say ... that if we had the results as in TEST C
... that we are more convinced that the null of 100 is NOT true ... than
for TEST B or TEST A?
no ifs, ands, or buts or it depends on this or that ... just straight
talking ... can we say this?
At 03:25 PM 1/30/01 +0000, Jerry Dallal wrote:
>dennis roberts wrote:
>
> > on page 2 of 10 ... they list summary points and, the one i quoted before
> > ... p values, or significance levels .. measure the strength of the
> > evidence against the null ...
>
>In a way, they do. Hwever, one has to be careful about specifying
>the way it which they measure it. For example, all other things
>being equal (sample size, in particular), the smaller the P value,
>the more discordant the data are with the hypothesis under test. (I
>don't doubt someone crafty will come up with a counter-example!), or
>to put it another way: All other things being equal, a smaller P
>value does not provide greater evidence in favor of the hypothesis
>under test. (Again, I'm waiting for the crafty counter.)
>
>
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_________________________________________________________
dennis roberts, educational psychology, penn state university
208 cedar, AC 8148632401, mailto:[EMAIL PROTECTED]
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