In article <[EMAIL PROTECTED]>,
Jerry Dallal  <[EMAIL PROTECTED]> wrote:
>Herman Rubin wrote:

>> If you, and your students, want to understand statistics,
>> do not start them out with ANY statistical procedures
>> until they understand probability (NOT how to calculate
>> probabilities) as well as evaluation of consequences and
>> probability modeling.

>For some unknown reason, today it struck me that if students
>*really* understood probability, there would be a period not
>survived by many that would begin with their asking, "Well, then,
>why go on?"

In a sense you can say that this is correct; if someone in
another field understands probability, probability modeling,
and the evaluation of consequences, a properly formulated
problem needs nothing more than calculation, assuming that
it is known how to calculate for that problem.  

Whatever decision rule is used can be summarized in the 
probability distribution of the results in each state of
nature.  Now there are reasons to condense and summarize
this information, but this is still largely probability.
Any justification of statistical procedures is based on
the probabilistic behavior of the results; expectation,
variance, etc., are probability concepts.

One could still ask which method of evaluation should be
used; this is not covered by probability.  And there is
the question of how to design the experiment; this uses
probability, but is not included.  So what is there in
statistics which is not essentially probability?

Now there are those who will be advancing the field, and
these should start with what is known and try to push
the frontier.  But it is still essentially probability.  
-- 
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, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED]         Phone: (765)494-6054   FAX: (765)494-0558
.
.
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