John, for myself and others who may be interested, can you tell us what other
"statistical methodology lists" are available?
Best,
Bill
John Maindonald wrote:
> Fisher is not the only person that it may be necessary
> to read 4 or 5 times. The same may be the case for
> side comments that Bill Venables is wont to make.
>
> Now to the parallel universe that I have in mind. I wonder
> whether the time is opportune for a list that focuses on
> "Statistical Methodology for R Users". The difference from
> other statistical methodology lists is that it will be
> assumed that list members have contact with, and an interest
> in, R. So the appearance of R code, and references to R
> documentation, would be entirely in place.
>
> One of the great things about R, and this email list, is
> that it has allowed methodological specialists from a
> professional statistical tradition to encounter application
> area specialists from areas that have developed their own
> relatively separate statistical tradition. Here we aim,
> primarily, to discuss R. I would like to see a place where
> those from the R community who wish discuss methodology,
> with R a secondary focus. We might, for example, talk about
> other things than R where there could be useful co-operative
> endeavour and exchange of ideas.
>
> --------------------------------------------------------------
>
> The best account I know of the separation of applied statistics
> into separate traditions, at least with respect to education
> and psychology, is in
> Gigerenzer et al. 1999. The Empire of Chance. Cambridge
> Univ Press.
>
> There is a lot more that could be added to what Gigerenzer at al
> say, but that book is a good start. There are books waiting to
> be written: 1) on the different traditions of multi-level
> modeling, generalizability theory etc, that have grown up in
> different application areas.
> 2) on the different notational conventions that have grown up
> in different areas.
>
> In reading Fisher, modern readers have the problem that he
> does not follow conventions that had not been invented (!)
> when he wrote. The diifficulty goes deeper. It is not all
> that obvious how the language, notational conventions and
> intellectual framework would change if for example his "The
> Design of Experiments" was to be completely rewritten for a
> modern audience. It would make quite a difference whether
> that audience was made up of field biologists or
> pyschologists. Professional statisticians, who were not the
> book's primary audience, are another matter again.
>
> John Maindonald email : john.maindonald at anu.edu.au
> Centre for Bioinformation Science, phone : (6125)3473
> c/o SMS, fax : (6125)5549
> John Dedman Mathematical Sciences Building (Building 27)
> Australian National University
> Canberra ACT 0200
> Australia
>
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