I like that advice. I also like to think of p's as measures of
reliability; a p of .001 is more likely to be replicated than a p of .1,
given the same effect size. 

Marty Bourgeois
University of Wyoming

-----Original Message-----
From: Karl L. Wuensch [mailto:wuenschk@;mail.ecu.edu] 
Sent: Monday, November 11, 2002 9:45 PM
To: Teaching in the Psychological Sciences
Subject: p is continuous, not dichotomous

Last I checked, the significance level, p, was a probability (the
conditional probability of obtaining results as more discrepant with the
null than are those in the current sample), and probabilities vary
CONTINUOUSLY from 0 to 1.  At least that is what Jack Cohen told me.

I suggest that we simply treat p as a measure of how well the data fit
with
the null hypothesis.  P = .08 is very poor fit, p = .04 is not much
poorer,
and p = .80 tells me that we got just about what we would expect were
the
null true.

Karl W.
----- Original Message -----
From: "G. Marc Turner" <[EMAIL PROTECTED]>
To: "Teaching in the Psychological Sciences" <[EMAIL PROTECTED]>
Sent: Monday, November 11, 2002 8:36 AM
Subject: Re: Marginally Significant?


In my mind, significance is an either/or situation. EIther you have it,
or
you don't. "Marginally significant", to me, would indicate something in
the
.048 range (assuming alpha=.05, it has to first be significant in order
to
be "marginally" so.)


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