Do keep in mind that random numbers are not random. It is a
deterministic procedure that produces them. In fact, for the typical random
number generator, if you run it twice with the same seed you will get exactly
the same two sets of "random" numbers.
Cheers,
[Karl L. Wuensch]<http://core.ecu.edu/psyc/wuenschk/klw.htm>
From: Rick Froman [mailto:[email protected]]
Sent: Friday, October 10, 2014 9:41 AM
To: Teaching in the Psychological Sciences (TIPS)
Subject: RE: [tips] Spurious Correlations
One thing I have found helpful in teaching the concept of spurious correlations
is to have students populate a number of columns in a spreadsheet with random
numbers and then calculate correlations between all the columns of random
numbers. Since they are random, the correlation in the population from which
all of these samples are drawn is 0. For every 100 correlations calculated in
this circumstance, using a .05 alpha level, students will find about five
spurious correlations that are statistically significant but are clearly
spurious (mind blown) :)
Rick
Dr. Rick Froman
Professor of Psychology
Box 3519
John Brown University
2000 W. University Siloam Springs, AR 72761
[email protected]<mailto:[email protected]>
(479) 524-7295
http://bit.ly/DrFroman
"The LORD detests both Type I and Type II errors." Proverbs
17:15<http://www.biblegateway.com/passage/?search=proverbs%2017:15&version=NIV>
-----Original Message-----
From: Mike Palij [mailto:[email protected]]
Sent: Friday, October 10, 2014 8:17 AM
To: Teaching in the Psychological Sciences (TIPS)
Cc: Michael Palij
Subject: re: [tips] Spurious Correlations
On Thu, 09 Oct 2014 18:23:19 -0700, Carol DeVolder wrote:
>Perhaps others are familiar with this site, but I wasn't. It's a fun
>collection of spurious correlations. Good for examples in class.
> http://tylervigen.com/
For people interested in such things, I suggest one take a look at some of
Brian Haig's writing on spurious correlations which provides a more "nuanced"
perspective on them (one can classify spurious correlation between those that
are truly spurious versus those that are not). Here's the reference for one of
his articles:
Haig, B. D. (2003). What is a spurious correlation?. Understanding
Statistics: Statistical Issues in Psychology, Education, and the Social
Sciences, 2(2), 125-132.
http://www.tandfonline.com/doi/abs/10.1207/S15328031US0202_03#preview:
or
http://psycnet.apa.org/psycinfo/2004-12710-003
A key point is whether a correlation represents a direct "effect" or
relationship (which is typically assumed in a correlational analysis) or an
indirect "effect" or relationship exists between two or more variables.
If we have three variables X, Y, and Z, and
(1) there is no direct relationship between X and Z
but
(2) there is an indirect relationship X -> Z -> Y
This raises thorny questions of mediation and moderation which I will leave to
Karl Wuensch to elaborate (or to provide access to his notes on the these
topics ;-).
Haig would probably call the correlations provided on the Tyler Vigen website
"nonsense correlations" but, for fans of the belief of "everything is connected
to everything else", one might refer to the "butterfly effect".
The butterfly effect refers to two conceptually unrelated events (apparently
nonsensical) but which are connected by a complex nonlinear relationship.
Simple correlational analysis that (a) do not have the necessary intermediate
variables, and/or (b) do not have the necessary nonlinear terms, will not
accurately represent the relationship or, more correctly, the process that
connects two variables.
Just something to think about. ;-)
-Mike Palij
New York University
[email protected]<mailto:[email protected]>
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