In article
<a4c12c0c-cea2-42f6-adb6-3bb066051ca5@[EMAIL PROTECTED]
>,
Hannele.Tervola@[EMAIL PROTECTED]
<Hannele.Tervola@[EMAIL PROTECTED]
> wrote:
>In science one makes observations and deduced based on them what the
>world is like and then makes some more observations to see if one's
>deductions are true or false. So the whole of science is based on the
>observations being correct and unbiased. It is the better the more
>sure one can be about the observations, so it is better to make as
>many sure observations as possible instead of the few only.
There is not just the problem of observations, but the
inferences made from the observations. It is NOT the
case that the observations determine the inferences made.
In simple cases, it may appear that this is so, but when
the cases are not so simple, good scientists can come up
with widely divergent models. It is at this point that
one can show that objectivity is not possible.
This lack of objectivity is treated in statistical decision
theory, and the answers are often that the answers are not
easy. This is not learned by starting out with apparently
simple cases, but by "plunging into the deep end."
Of course, one will need flotation devices and diving bells,
and so the abstract concepts of logic, mathematics, probability,
and "mathematical" statistics are needed. It is the concepts,
not the ability to solve simple problems, which are im****tant.
Knowing what addition means and when to use it is im****tant;
knowing how to perform the addition is useful, but not very
im****tant.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Department of Statistics, Purdue University
hrubin@[EMAIL PROTECTED]
Phone: (765)494-6054 FAX: (765)494-0558
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