[tips] 2014 Tipsters of the year

2014-12-11 Thread michael sylvester
Christo
James Clark
Stephen Black
St.Andrew's Collge Psychology faculty
for voting to remain in the UK

Patrons at McKelvie's Glenlevich scotch
whiskey pub rhymimg in the Glomond

Hughes the Australian cricketer- gone but not forgotten
The Cuban government for having sent
the largest contingent of medical doctors and personnel to manage
ebola in  Africa

To the Archbishop of Canterbury who was not aware that there was homelessness 
in London

Malala

Checks are in the mail
michael
daytona beach,florida

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[tips] curious statistical reasoning

2014-12-11 Thread Ken Steele


A colleague sent me a link to an article -

https://www.insidehighered.com/news/2014/12/10/study-finds-gender-perception-affects-evaluations

I took a look at the original article and found this curious footnote.

Quoting footnote 4 from the study:

While we acknowledge that a significance level of .05 is conventional 
in social science and higher education research, we side with Skipper, 
Guenther, and Nass (1967), Labovitz (1968), and Lai (1973) in pointing 
out the arbitrary nature of conventional significance levels. 
Considering our study design, we have used a significance level of .10 
for some tests where: 1) the results support the hypothesis and we are 
consequently more willing to reject the null hypothesis of no 
difference; 2) our hypothesis is strongly supported theoretically and by 
empirical results in other studies that use lower significance levels; 
3) our small n may be obscuring large differences; and 4) the gravity of 
an increased risk of Type I error is diminished in light of the benefit 
of decreasing the risk of a Type II error (Labovitz, 1968; Lai, 1973).


Ken


Kenneth M. Steele, Ph. D.steel...@appstate.edu
Professor
Department of Psychology http://www.psych.appstate.edu
Appalachian State University
Boone, NC 28608
USA


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[tips] Cognitive Psych position

2014-12-11 Thread Gerald Peterson
Tipsters, FYI and helpful distribution:

Assistant Professor of Psychology
 
SVSU invites applications for a tenure-track assistant professor position to 
begin July 1, 2015. The successful candidate will demonstrate excellence in 
teaching, expertise in cognitive psychology, and competence in experimental 
psychology.  Candidates are expected to have an active research agenda to which 
undergraduates may contribute. Candidates should be prepared and willing to 
teach undergraduate courses such as Cognitive Processes, Sensation and 
Perception, Experimental Design, Statistics, and General Psychology, as well as 
courses in their specific areas of expertise. The teaching load is 24 credit 
hours/year (12/12) at the undergraduate level.  Other responsibilities include 
supervising undergraduate research/honors projects, academic service, and 
advising.  For complete list of requirements, further information, and to apply 
for this position, please visit www.jobs.svsu.edu.  Applicants must apply 
on-line.  SVSU is an EO/AA employer.

 
G.L. (Gary) Peterson,Ph.D
Psychology@SVSU


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RE: [tips] curious statistical reasoning

2014-12-11 Thread Jim Clark
Hi

Seems like they could have gotten to the same point (perhaps) by using a 
directional hypothesis given points 1  2? Unless the .10 is directional and 
the non-directional p is .20?

3 does not make a lot of sense to me given p is sensitive to n?
4 might be an appropriate consideration given the consequences of the two 
possible errors. Not enough info here.

Take care
Jim


Take care
Jim

Jim Clark
Professor  Chair of Psychology
204-786-9757
4L41A

-Original Message-
From: Ken Steele [mailto:steel...@appstate.edu] 
Sent: Thursday, December 11, 2014 1:19 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: [tips] curious statistical reasoning


A colleague sent me a link to an article -

https://www.insidehighered.com/news/2014/12/10/study-finds-gender-perception-affects-evaluations

I took a look at the original article and found this curious footnote.

Quoting footnote 4 from the study:

While we acknowledge that a significance level of .05 is conventional in 
social science and higher education research, we side with Skipper, Guenther, 
and Nass (1967), Labovitz (1968), and Lai (1973) in pointing out the arbitrary 
nature of conventional significance levels. 
Considering our study design, we have used a significance level of .10 for some 
tests where: 1) the results support the hypothesis and we are consequently more 
willing to reject the null hypothesis of no difference; 2) our hypothesis is 
strongly supported theoretically and by empirical results in other studies that 
use lower significance levels;
3) our small n may be obscuring large differences; and 4) the gravity of an 
increased risk of Type I error is diminished in light of the benefit of 
decreasing the risk of a Type II error (Labovitz, 1968; Lai, 1973).

Ken


Kenneth M. Steele, Ph. D.steel...@appstate.edu
Professor
Department of Psychology http://www.psych.appstate.edu
Appalachian State University
Boone, NC 28608
USA


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RE: [tips] curious statistical reasoning

2014-12-11 Thread Rick Froman
I think the main point is that this was basically designed to be a small pilot 
study so why even publish it? 

It is interesting that they decided to go with Welch's t (not assuming equal 
variances) for all of the calculations no matter what the variances were. With 
respect to Jim's inquiry, the probabilities seem to have been non-directional. 
In the case of the overall student rating index, a regular t test assuming 
equal variances would have produced a significant (p.05) result (ignoring the 
fact that they did 26 t tests). Also, since they did 26 t test comparisons (of 
which only three were significant at .05 and another three at .10), the 
Bonferroni correction would actually call for a more stringent alpha of .0019 
instead of inflating it further to .10.

On number three, I like how they said that they used a .10 significance level 
on some tests. I hope I am not being too cynical in believing that the ones 
they used a .10 significance level corresponded entirely with the ones where p 
was greater than .05 but less than .10. As to point four, there is a way to 
simultaneously decrease the probability of making a Type II error and increase 
the probability of making a Type I error: increase your sample size. Which 
brings me back to the first point. This was correctly conceived of as a pilot 
study so why stretch the stats and rush it to print?

Rick

Dr. Rick Froman
Professor of Psychology
Box 3519
x7295
rfro...@jbu.edu  
http://bit.ly/DrFroman 


-Original Message-
From: Jim Clark [mailto:j.cl...@uwinnipeg.ca] 
Sent: Thursday, December 11, 2014 4:18 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: RE: [tips] curious statistical reasoning

Hi

Seems like they could have gotten to the same point (perhaps) by using a 
directional hypothesis given points 1  2? Unless the .10 is directional and 
the non-directional p is .20?

3 does not make a lot of sense to me given p is sensitive to n?
4 might be an appropriate consideration given the consequences of the two 
possible errors. Not enough info here.

Take care
Jim


Take care
Jim

Jim Clark
Professor  Chair of Psychology
204-786-9757
4L41A

-Original Message-
From: Ken Steele [mailto:steel...@appstate.edu] 
Sent: Thursday, December 11, 2014 1:19 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: [tips] curious statistical reasoning


A colleague sent me a link to an article -

https://www.insidehighered.com/news/2014/12/10/study-finds-gender-perception-affects-evaluations

I took a look at the original article and found this curious footnote.

Quoting footnote 4 from the study:

While we acknowledge that a significance level of .05 is conventional in 
social science and higher education research, we side with Skipper, Guenther, 
and Nass (1967), Labovitz (1968), and Lai (1973) in pointing out the arbitrary 
nature of conventional significance levels. 
Considering our study design, we have used a significance level of .10 for some 
tests where: 1) the results support the hypothesis and we are consequently more 
willing to reject the null hypothesis of no difference; 2) our hypothesis is 
strongly supported theoretically and by empirical results in other studies that 
use lower significance levels;
3) our small n may be obscuring large differences; and 4) the gravity of an 
increased risk of Type I error is diminished in light of the benefit of 
decreasing the risk of a Type II error (Labovitz, 1968; Lai, 1973).

Ken


Kenneth M. Steele, Ph. D.steel...@appstate.edu
Professor
Department of Psychology http://www.psych.appstate.edu
Appalachian State University
Boone, NC 28608
USA


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RE: [tips] curious statistical reasoning

2014-12-11 Thread Rick Froman
In my last paragraph, I meant to say that there is a way of decreasing the 
probability of making a Type II error without increasing the probability of 
making a Type I error: increase the sample size.



Dr. Rick Froman

Professor of Psychology

Box 3519

x7295

rfro...@jbu.edu

http://bit.ly/DrFroman



-Original Message-
From: Rick Froman [mailto:rfro...@jbu.edu]
Sent: Thursday, December 11, 2014 5:00 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: RE: [tips] curious statistical reasoning



I think the main point is that this was basically designed to be a small pilot 
study so why even publish it?



It is interesting that they decided to go with Welch's t (not assuming equal 
variances) for all of the calculations no matter what the variances were. With 
respect to Jim's inquiry, the probabilities seem to have been non-directional. 
In the case of the overall student rating index, a regular t test assuming 
equal variances would have produced a significant (p.05) result (ignoring the 
fact that they did 26 t tests). Also, since they did 26 t test comparisons (of 
which only three were significant at .05 and another three at .10), the 
Bonferroni correction would actually call for a more stringent alpha of .0019 
instead of inflating it further to .10.



On number three, I like how they said that they used a .10 significance level 
on some tests. I hope I am not being too cynical in believing that the ones 
they used a .10 significance level corresponded entirely with the ones where p 
was greater than .05 but less than .10. As to point four, there is a way to 
simultaneously decrease the probability of making a Type II error and increase 
the probability of making a Type I error: increase your sample size. Which 
brings me back to the first point. This was correctly conceived of as a pilot 
study so why stretch the stats and rush it to print?



Rick



Dr. Rick Froman

Professor of Psychology

Box 3519

x7295

rfro...@jbu.edumailto:rfro...@jbu.edu

http://bit.ly/DrFroman





-Original Message-

From: Jim Clark [mailto:j.cl...@uwinnipeg.ca]

Sent: Thursday, December 11, 2014 4:18 PM

To: Teaching in the Psychological Sciences (TIPS)

Subject: RE: [tips] curious statistical reasoning



Hi



Seems like they could have gotten to the same point (perhaps) by using a 
directional hypothesis given points 1  2? Unless the .10 is directional and 
the non-directional p is .20?



3 does not make a lot of sense to me given p is sensitive to n?

4 might be an appropriate consideration given the consequences of the two 
possible errors. Not enough info here.



Take care

Jim





Take care

Jim



Jim Clark

Professor  Chair of Psychology

204-786-9757

4L41A



-Original Message-

From: Ken Steele [mailto:steel...@appstate.edu]

Sent: Thursday, December 11, 2014 1:19 PM

To: Teaching in the Psychological Sciences (TIPS)

Subject: [tips] curious statistical reasoning





A colleague sent me a link to an article -



https://www.insidehighered.com/news/2014/12/10/study-finds-gender-perception-affects-evaluations



I took a look at the original article and found this curious footnote.



Quoting footnote 4 from the study:



While we acknowledge that a significance level of .05 is conventional in 
social science and higher education research, we side with Skipper, Guenther, 
and Nass (1967), Labovitz (1968), and Lai (1973) in pointing out the arbitrary 
nature of conventional significance levels.

Considering our study design, we have used a significance level of .10 for some 
tests where: 1) the results support the hypothesis and we are consequently more 
willing to reject the null hypothesis of no difference; 2) our hypothesis is 
strongly supported theoretically and by empirical results in other studies that 
use lower significance levels;

3) our small n may be obscuring large differences; and 4) the gravity of an 
increased risk of Type I error is diminished in light of the benefit of 
decreasing the risk of a Type II error (Labovitz, 1968; Lai, 1973).



Ken





Kenneth M. Steele, Ph. D.
steel...@appstate.edumailto:steel...@appstate.edu

Professor

Department of Psychology http://www.psych.appstate.edu

Appalachian State University

Boone, NC 28608

USA





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