On 21 Apr 2001 13:04:55 -0700, [EMAIL PROTECTED] (Will Hopkins)
wrote:
> I've joined this one at the fag end. I'm with Dennis Roberts. The way I
> would put it is this: the PRINCIPLE of a sampling distribution is actually
> incredibly simple: keep repeating the study and this is the sort of spread
> you get for the statistic you're interested in. What makes it incredibly
> simple is that I keep well away from test statistics when I teach stats to
> biomedical researchers. I deal only with effect (outcome) statistics. I
> even forbid my students and colleagues from putting the values of test
> statistics in their papers. Test statistics are clutter.
>
> The actual mathematical form of any given sampling distribution is
> incredibly complex, but only the really gifted students who want to make
> careers out of statistical research need to come to terms with that. The
So you guys are all giving advice about teaching statistics to
psychology majors/ graduates, who have no aspirations or
potential for being anything more than "consumers" (readers)
of statistics? Or (similar intent) to biomedical researchers?
Don't researchers deserve to be shown a tad more?
A problem that I have run into is that Researchers who are
well-schooled in the names and terms of procedures
don't always recognize the leap to "good data analysis."
Actually, that can be true about people trained as biostatisticians,
too, despite a modicum of exposure to case studies and Real Data,
and I suspect it is *usually* true about people just emerging
from training as mathematical statisticians.
Just a couple of thoughts.
> rest of us just plug numbers into a stats package or spreadsheet. I'm not
> sure what would be a good sequence for teaching the mathematical
> forms. Binomial --> normal --> t is probably as good as any.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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