Might be worth looking at:
Gigerenzer, G. (2004) Mindless Statistics. The Journal of
Socio-Economics, 33, , 587-606.
http://www.google.co.nz/url?q=http://www-unix.oit.umass.edu/~bioep740/yr
2009/topics/Gigerenzer-jSoc-Econ-1994.pdf
<http://www.google.co.nz/url?q=http://www-unix.oit.umass.edu/~bioep740/y
r2009/topics/Gigerenzer-jSoc-Econ-1994.pdf&ei=h25GS9qlCY_o7APe89Bt&sa=X&
oi=spellmeleon_result&resnum=1&ct=result&ved=0CAcQhgIwAA&usg=AFQjCNFEizs
XgWL6776JK0jcWKmOdeWGuw>
&ei=h25GS9qlCY_o7APe89Bt&sa=X&oi=spellmeleon_result&resnum=1&ct=result&v
ed=0CAcQhgIwAA&usg=AFQjCNFEizsXgWL6776JK0jcWKmOdeWGuw
Abstract
Statistical rituals largely eliminate statistical thinking in the social
sciences. Rituals are indispensable for identification with social
groups, but they should be the subject rather than the procedure of
science. What I call the "null ritual" consists of three steps: (1) set
up a statistical null hypothesis, but do not specify your own hypothesis
nor any alternative hypothesis, (2) use the 5% significance level for
rejecting the null and accepting your hypothesis, and (3) always perform
this procedure. I report evidence of the resulting collective confusion
and fears about sanctions on the part of students and teachers,
researchers and editors, as well as textbook writers..
With the "interesting" quote at the head of the paper from R.A. Fisher
". . . no scientific worker has a fixed level of significance at which
from year to year, and in all circumstances, he rejects hypotheses; he
rather gives his mind to each particular case in the light of his
evidence and his ideas. Sir Ronald A. Fisher (1956)"
Try this as well from p. 589
"Fisher is mostly blamed for the null ritual. But toward the end of his
life, Fisher (1955, 1956) rejected each of its three steps.
First, "null" does not refer to a nil mean difference or zero
correlation, but to any hypothesis to be "nullified." A correlation of
0.5, or a reduction of five cigarettes smoked per day, for instance, can
be a null hypothesis.
Second, as the epigram illustrates, by 1956, Fisher thought that using a
routine 5% level of significance indicated lack of statistical
sophistication. No respectable researcher would use a constant level.
Your chances of finding this quote in a statistical text in psychology
is virtually nil.
Third, for Fisher, null hypothesis testing was the most primitive type
of statistical analyses and should be used only for problems about which
we have no or very little knowledge (Gigerenzer et al., 1989, chapter
3). "
Incredible really.
Regards .. Paul
pbarrett.net
Advanced Projects R&D
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> -----Original Message-----
> From: A UK-based worldwide e-mail broadcast system mailing list
> [mailto:[log in to unmask]] On Behalf Of Burke Johnson
> Sent: Friday, January 08, 2010 11:23 AM
> To: [log in to unmask]
> Subject: Question about a particular p-value
>
> Hello list members,
>
> I have a question for you: Would you advocate "case 1" or "case 2"
below
> (or do you have a preferred "case 3")?
>
> Case 1.
> If p is less than or equal to alpha, then reject null.
> If p is greater than alpha, then fail to reject null.
>
> Case 2.
> If p is less than alpha, then reject null.
> If p is greater than or equal to alpha, then fail to reject null.
>
> As you can see, for completeness I'm asking for your thoughts about
the
> highly unlikely (but possible) situation where p=alpha.
>
> For example, when using an alpha level of .05, what would you do in
the
> unlikely situation where the observed p-value is equal to .05 (i.e.,
> alpha is set at .05 and the observed p=.05 to as many places as the
> computer prints out).
>
> If you recommended case 1, I have a follow-up question about rounding:
> What observed p-value would you consider close enough to be considered
> "equal to .05" in the procedure? (The late Jacob Cohen offered a
> convention that a p-value of .00 to .05 was sufficiently small, but
.051-
> 1.00 was not sufficiently small to reject the null).
>
> Thanks in advance for your thoughts!
>
> Burke Johnson
>
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