ABSQOLUTELY!

WT

PS: "It's no use, Professor Agassiz, it's turtles all the way down!" --A woman who asserted that the earth rested upon the back of a giant turtle, and made this remark when Agassiz asked ". . . upon what, then, madam, does the turtle rest?" "Another turtle, of course," the woman kept responding. (At least this is how I remember the story.)

McCallum has touched upon the reason why I have suggested to the Smithsonian Library of Life project that they accumulate data on the ranges of organism's requirements and limitations.


----- Original Message ----- From: "malcolm McCallum" <[email protected]>
To: <[email protected]>
Sent: Friday, October 12, 2012 8:16 PM
Subject: Re: [ECOLOG-L] correlation v. causation


The whole point of a correlation is that you don't really know what is
going one with two or more variables, but you think there might be a
relationship of some kind. That is why we say correlation doesn't
indicate causation.
A regression does indicate causation because we name a determinant
variable.  For example, if you take a bunch of guppies in a glass of
water and add salt until the die, then you are testing to see how much
salt kills guppies.  You do a regression.  However, if you go out in
the wilderness and measure salt concentrations and count guppies for
unrelated reasons, and after looking at your data you say, hey it
looks like guppies might be getting killed by salt, you still do a
regression because you are looking for the effect of salt on guppies,
it sure isn't very logical even if narrowly possible that guppies are
changing the salt concentration of the water.  Now, if you are doing
measurements on all kinds of data.  YOu happen to notice that a lot of
guppies are in ponds that also have plants.  You have no idea if the
plants are helping the guppies, if the guppies are helping the plants,
or if some third factor is influencing both of their apperaance.  SO,
you run a correlation to see if the association you seem to observe is
actually happening.  Later, you can set up experimetns to determine
why plants and guppies have correlated presence absence rates. In
those following experiments you might use a regression.  (this all
assumes you have the experiment set up properly for the tests I
mention!!!! :)

Make sense?

On Tue, Oct 9, 2012 at 12:56 PM, Wayne Tyson <[email protected]> wrote:
Hi y'all,

If I remember the quote correctly, it said "Correlation is not causation." It did not say that it didn't imply causation. The distinction is crucial, eh? (It appears that my initial response to the initial question didn't make its way to Ecolog, possibly because I neglected to approve it or because it
was rejected.

WT

PS: Correlation is not in opposition to (v.) causation.

Let us not jump to contusions.

----- Original Message ----- From: "Devan McGranahan"
<[email protected]>
To: <[email protected]>
Sent: Tuesday, October 09, 2012 8:57 AM

Subject: Re: [ECOLOG-L] correlation v. causation


Hi Shelley, others,

Slate recently had a great article on correlation and causation with a
historical perspective.

My favorite line: "'No, correlation does not imply causation, but it
sure as hell provides a hint."


http://www.slate.com/articles/health_and_science/science/2012/10/correlation_does_not_imply_causation_how_the_internet_fell_in_love_with_a_stats_class_clich_.html







"Having nothing better to do, I set fire to the prairie."
-- Francis Chadron, 1839, Fort Clark, North Dakota

http://www.devanmcgranahan.info


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--
Malcolm L. McCallum
Department of Molecular Biology and Biochemistry
School of Biological Sciences
University of Missouri at Kansas City

Managing Editor,
Herpetological Conservation and Biology

"Peer pressure is designed to contain anyone with a sense of drive" -
Allan Nation

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1990's:  Many fish stocks depleted due to overfishing, habitat loss,
           and pollution.
2000:  Marine reserves, ecosystem restoration, and pollution reduction
         MAY help restore populations.
2022: Soylent Green is People!

The Seven Blunders of the World (Mohandas Gandhi)
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Knowledge w/o character
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Science w/o humanity
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