"Esa M. Rantanen" wrote:
>
> Dear All,
>
> I have been exasperated by a particular deficiency (in my view) of
> many graduate students in dealing with their data, namely, delving
> into often complex statistical analyses without first having a good
> 'feel' of where the data came from and what they should be looking
> for. I was recently 'venting' my frustration to a colleague, who
> will be teaching a two-course graduate stats 'package' in the near
> future. We discussed ways to impress the importance of 'looking at
> the data' on the students. I would like to pose the same questions
> to members of this list; specifically,
To me it happend the reverse way, sometimes. People looking at data
and not knowing, what to do...
>
> (1) how do you rate the importance of exploratory and (in particular)
> graphical analysis of data
my rating: high
> prior to doing inferential statistics, and
my rating: it depends on the background, that people have.
>
> (2) how do you (or, would) incorporate these aspects of statistics
> into your teaching?
>
My current praxis is, to mix this with the tendency to be able to
lengthen the phases, in which one of the methods dominate. So some-
times you can say, the "view into data" precedes the theoretical methods,
another time, the next phase you can say the opposite. ;-)
Generally, in exploring the world, you go from some observations
to some theory to some better observations to some better theory.
Practically -
we start our course with an overview on history and some
introduction of known and not-so-known termini of statistics, just for
a sketch of the base-walls of the building.
Next lesson we discuss three concurrent survey-abstracts and learn
by that (usually controversal and lively) discussion the problem of
formulating goals and self-reflect hypotheses and a-priori knowledge.
After exercises (detailing the explicit questions needed to be able to
explore/document data and/or study the hypotheses) the method changes
to a more lecture format about scale metrics and their rationale.
>From measures of central tendency the next phase is then more
practical again, when the "display of data" and of compressed infor-
mation is the subject. This time I'll let the students produce graphics
with a simulated database according to some basic questions from the
start-discussions. And so on...
I find it important for my introductory course, that students get
contact with both views of the things.
I recognize also types of student, whose main mental access to the
subject is either more practical or more theoretical. To get them
to recognize also the charme of their non-familiar method often produces
very positive feedback and is then an achievement of new abilities
and mental instruments besides of the additional knowledge. This
is, in my opinion, essential and the main goal of the "hidden"
curriculum in introductory courses.
Gottfried Helms
.
.
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