Seems to me that hypothesis testing remains an essential step. Take for
instance the following data that I made up just for the purpose of
illustration and the correlation matrix it produces:
VAR1 VAR2
2.00 2.00
3.00 2.00
5.00 6.00
4.00 2.00
3.00 1.00
Correlations
VAR1 VAR2
VAR1
Pearson Correlation 1.000 .765
Sig. (2-tailed) . .132
N 5 5
VAR2
Pearson Correlation .765 1.000
Sig. (2-tailed) .132 .
N 5 5
Now, .77 is probably a respectable correlation (depending of course on the
application). However, the question here is how much faith we have in this
estimate. Accepting the traditional alpha level of .05 (because it is not
real data and so no reason not to) we would say that this is beyond what we
will accept as the risk of making a Type I error, so we fail to reject the
null. This is not to say that the correlation is zero, but for practical
purposes with this sample, we must treat it as no effect (and here probably
take into consideration our power). Effect size is useless without
significance. Significance is meaningless without information on effect
size.
-----Original Message-----
From: dennis roberts [mailto:[EMAIL PROTECTED]]
Sent: Monday, April 10, 2000 1:35 PM
To: [EMAIL PROTECTED]
Subject: Re: hyp testing
At 01:16 PM 4/10/00 -0300, Robert Dawson wrote:
>both leave the listener wondering "why 0.5?" If the only answer is "well,
>it was a round number close enough to x bar [or "to my guesstimate before
>the experiment"] not to seem silly, but far enough away that I thought I
>could reject it." then the test is pointless.
>
> -Robert Dawson
YOU HAVE made my case perfectly! ... this is why the notion of hypothesis
testing is outmoded, no longer useful ... not worth the time we put into
teaching it ...
in the case above ... i would ask:
what is the population rho value ... THAT is the important inferential
issue ...
there is no reason why we would have to say: i wonder if it is .5 ... let's
TEST that, or ... i wonder if it is .7 ... let's TEST that ...
we can simply ask the question and try to get an answer to that ... and
there is no need to test a pre formulated null to get some sensible answer
to the question
no need for ANY null ... therefore no need for any hypothesis test
if 0 is absurd ... and, if i hypothesized .5 and you ask why .5??? then we
could have asked anywhere from 0 to .5 ... and they would have been just as
non functional ...
that's it ... hypothesis testing is non functional
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