Often those correlations called spurious are just those for which we
don't know enough to explain why the covary. That correlation between human
and stork populations was set into motion by unknown events that took place at
the time of the Big Bang.
More proximally, it has been suggested that as human population
increased so did the number of roofs where storks like to nest.
Cheers,
Karl L. Wuensch
-----Original Message-----
From: Mike Palij [mailto:m...@nyu.edu]
Sent: Friday, October 10, 2014 9:17 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
m...@nyu.edu
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