[rearranging this note, to put the posts into order, earliest first. ]
> > At 07:44 AM 02/29/2000 -0800, Ward Soper wrote:
> > >After one learns to do the textbook problems, as in Freund's
> > >Mathematical Statistics, where should one turn to learn what tests to
> > >use in various situations and how to design studies? Can anyone suggest
> > >some good texts or other resources?
===============
> dennis roberts wrote:
> >
> > william trochim's research methods knowledge base is a good place to start
> > ... to get ideas
> >
> > http://trochim.human.cornell.edu/kb/
================
On 29 Feb 2000 17:48:07 -0800, [EMAIL PROTECTED]
(Paul Gardner) wrote:
> George. M. Diekhoff, Basic Statistics for the Social and Behavioral
> Sciences, Prentice Hall, 1996, has an excellent chapter at the end which
> presents a decision tree. This summarises the various statistical
> procedures in the text and helps learners to determine which statistics
> are appropriate under various conditions.
=================
- Pardon; I haven't seen Diekoff, but 'decision tree' sounds too
cheap. There is certainly a place for a mechanical framework of tests
and procedures; but I read the original question as less particular
than that, and more general ("how to design studies"); and the first
answer, that way, too.
An enormous decision tree may give the right technical answer to 100%
of the narrow questions, but -- since it takes knowledge to frame the
right question -- that will be a misleading answer, I would guess, for
1/3 of the naive questioners, at least. People just can't tell you
what they never thought to ask, concerning
'reliability' (of various kinds);
'dependence' (ditto);
'shape of the distribution';
'outliers'; and
'What numbers are meaningful when we use this measurement?' or,
'What transformations might be useful?'
(I am still answeriing the big question, Why can't a computer give us
all the stats advice that we need? So far, no one has programmed a
computer with 10,000 well-classified examples....)
If they have not learned the whole statistical vocabulary, they won't
be able to argue persuasively that their own answers are correct. And
you can't thoroughly learn the vocabulary until you are expert enough
to know something about all the available techniques.
In addition to the statistics, there are particular problems in each
area about their own sorts of statistical designs. To learn what to
do in various situations, I think you have to *read*, you have to be
exposed to a large number of various situations. You have to read
some good examples, and you have to read criticisms which include
examples that were not-so-good.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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