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