Dear Tipsters, Cowles and Davis (1982) wrote an excellent paper on the origins of the .05 convention. It is interesting to see the position that some of the great statisticians took on where the issue of where to set a guideline for siginificant. For example, referring to chi square, Pearson wrote that the fit is "remarkably good" if p = .56, and "not very improbable" if p .1.
American Psychologist, 37, 553-558.
Sincerely,
Stuart
___________________________________________________________________________
"Floreat Labore"
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"Recti cultus pectora roborant"
Stuart J. McKelvie, Ph.D., Phone: 819 822 9600 x 2402
Department of Psychology, Fax: 819 822 9661
Bishop's University,
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E-mail: stuart.mckel...@ubishops.ca<mailto:stuart.mckel...@ubishops.ca> (or
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Floreat Labore"
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___________________________________________________________________________
From: William Scott [mailto:wsc...@wooster.edu]
Sent: April 22, 2013 4:01 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: Re: [tips] Polling...
To me, the phrase "approaching significance" implies that all we need to do is
run a few more subjects until we see significance, a practice known to bolster
your chances for a type I error.
Bill Scott
>>> Claudia Stanny 04/22/13 1:28 PM >>>
"Highly significant" conflates statistical rarity with impact (importance of
the effect, the size of the effect).
On the other hand, I think "approaching significance" can be useful and I will
defend that practice (although I wouldn't push its use in a publication).
Many statisticians note the arbitrariness of the decision criterion (the
magical .05) and argue that a result that would occur randomly with a
probability of .051 or .052 or .06 (I could go on . . . it is a slippery slope)
deserves closer examination than just deciding that the result is does not meet
the criterion to be declared statistically reliable. This rigidness in the
decision process seems to reinforce the too-common treatment of statistical
analysis as a ritual of taking out data (our sacrificial goat, as it were) to
the oracle for a decision. We can be more thoughtful than this. (Abelson's
excellent book, Statistics as Principled Argument, has some discussion of the
thoughtful use of inferential statistics.)
Failure to reach the criterion can occur for reasons other than absence of an
effect. The near misses are worth examining. Similarly, the just-made-it
"successes" deserve replication and questions about Type I Errors.
Claudia
_____________________________________________
Claudia J. Stanny, Ph.D.
Director
Center for University Teaching, Learning, and Assessment
Associate Professor
NSF UWF Faculty ADVANCE Scholar
School of Psychological and Behavioral Sciences
University of West Florida
11000 University Parkway
Pensacola, FL 32514 - 5751
Phone: (850) 857-6355 (direct) or 473-7435 (CUTLA)
csta...@uwf.edu<mailto:csta...@uwf.edu>
CUTLA Web Site: http://uwf.edu/cutla/
Personal Web Pages: http://uwf.edu/cstanny/website/index.htm
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