My point is that correlation cannot show causation.
By correlating chance occurrences of any trait, set
of traits, specific causative agents, specific
behaviors, etc, one cannot ever show that there is a
"thing" which exists so as to continue; in fact, the
"logic" used must always result in the answer that
there is not a thing being studied but only that
there are two (or more) things whose characteristics
might be described using a third (hidden) variable.
I am not surprised that you do not understand what I
am saying, it is not "like" anything (not correlated
to another argument); instead, it is an ontological
development of a logical sort whose ordering is
found in the meaning of the words themselves and the
way that the words necessarily add up to show an
inconsistency in the theoretical conclusion if the
conclusion (as stated in the words) purports to be
an effect of the mental processes which lawfully
create them.
Again, "chance recombination" cannot speak to an
objective manifestation except according to
"not-null". Competition is similarly a zero sum
game. Any *thing* "survival" must have a 100%
probability in reference to itself that it has
survived; thus, one cannot speak of a survival
mechanism which has a chance probability of not
existing nor of being in competition with itself.
You might speak about "blue eyes" surviving as
correlated with "brown eyes", but you cannot speak
of a survival mechanism for all, or any, trait-- in
an *explanatory* (rather than an applied) theory as
being "the chance combination of all possibilities"
and say that this results in *any* specific trait.
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>At 11:21 PM 5/10/98 PDT, B. Lane Robertson wrote:
>>It took me a long time to understand what little
>>statistics I understand. The sciences are based on
>>a certain kind of math. The way this is done is to
>>take a group (all first graders), measure a behavior
>>(give them a grade for spelling their name), make
>>this into a math formula which adds the scores and
>>divides by the number of students, and come up with
>>an average score. Then, they take each student and
>>compare their score to the average to find out how
>>far their actual scores differ from the average.
>
>I understand the essence and principles of statistics
>and probability theory, and do not require a tutorial,
>but thanx anyway. What I was trying to say was that
>I needed specific examples for specific statements
>and assertions. Read on:
>
>>In my explanation, I was trying to show that the
>>*average score* is not a REAL score (none of the
>>students actually scored this number-- though it
>>might be written like a test score, ie. 50%). The
>>score is a *relationship* between all of the
>>students and does not represent any of them... all
>>of the real scores are shown as a deviation from
>>this number-- even if this deviation is zero (which
>>says that even if a student scored 50% he is not
>>represented by this average, but deviates from this
>>score by .0). All student scores are then plotted
>>around this mean score according to a "normal
>>distribution" which looks like a bell on an x,y
>>graph-- big where the vertical axis crosses the
>>horizontal but slanting down toward both ends until
>>there are only a few students represented at either
>>end of the horizontal axis (the central point is the
>>average score and does not represent any student,
>>all students fall to either side of this point...
>>though maybe .0 to the side of it, as above).
>
>As in the current thread on "infinity', care must be
>taken when attempting to use abstract mathematical
>formulations to describe the real world. Is it the
>right tool to use in this situation? Is it properly
>applied within the context of the real-world dynamics
>of whatever it is you're trying to formalize
>mathematically?
>
>>The theory of Darwinian evolution is also based on
>>this reasoning. The theory says that there are
>>certain traits which form a relationship around an
>>average. This relationship is called "chance
>>recombination".
>
>This is what I mean about specific examples for
>specific statements. I'm not sure what you're referring
>to here, so I can't evaluate it. By "traits", do you
>mean "expressed traits", such as eye color or gender,
>or do you mean the transcribed results of any "gene",
>such as protein precursors, and what reasoning do you
>use to group whatever factors you're talking about
>before you ascribe a relationship based on averages?
>What is averaged, and why?
>
>>Chance recombination says that for
>>all traits (like for all student scores)
>
>This is analogy. To be able to evaluate whether
>the statistical application or treatment is
>appropriate in these circumstances, example is
>required. By "chance recombination", are you
>referring to chromosomal recombination? If so,
>how does this treat organisms that don't
>express chromosomal recombination? How is the
>"chance" factor stated here, different from the
>chance element represented by random mutation
>discussed later on? What rationale do you use
>to make the distinction?
>
>>there is a
>>"normal curve" which can be drawn. The central
>>point, "survival", does not represent any trait (or
>>any individual, etc.).
>
>Assuming the application of the statistical analysis
>is accurate and appropriate (that is, it precisely
>and concisely reflects objective reality), what
>value is it, exactly, that is plotted on this
>curve, and by what justification do you assign the
>centre with the property of "survival"? Survival
>of what? The gene? The Alelle? The organism? The
>population?
>
>>On either side of center
>>there is a deviation of plus or minus.
>> "Competition" says that the traits with a plus
>>exactly compete with the traits with a minus so that
>>the center point can continue to represent "no
>>trait".
>
>I still don't understand, B.
>Sorry.
>
>Dan
>
B. Lane Robertson
Indiana, USA
http://www.window.to/mindrec
AAA000
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