[R] Terminology and canonical statistical user literature

[Tom Blackwell]

Dr. Prechelt  -

It's been my observation that there IS no book of the sort
you have asked for.  There have been many attempts over the
last 75 years to write such a book.  Attempts by some very
smart and articulate people  . . .  and no such attempt that
I know of has succeeded.

I am forced to conclude that there is something intrinsic to
the subject matter which makes it refractory to a good textbook
exposition.  We can speculate about what that is, but I think
the evidence is plain that there is some inherent difficulty.

The way which does seem to work in learning this material is
a spiral - do an introductory look with a limited set of basic
statistical procedures.  Don't worry if you didn't understand
quite all of the details.  Let it sit for a few months;  find
an applied situation where you just HAVE to make use of what
you know.  Then, three months later, go back and view all of
the same procedures again, from a somewhat more sophisticated
or abstract viewpoint, and extend your knowledge to a few more
procedures.

This approach to learning statistics does seem to work, but
it's not a quick process.  I don't know of any other.

-  tom blackwell  -  u michigan medical school  -  ann arbor  -

On Tue, 16 Mar 2004, Lutz Prechelt wrote:

> Brian Ripley wrote (to somebody asking about "effect sizes"):
> > ...
> > Given that, I wonder if you are used to standard terminology.
>
> Good point. But I think for many of us there is more behind that.
>
> I personally belong to an (apparently fairly large) group of
> R users who may be enthusiastic, but are statistical laymen
> due to a lack of formal education in the area.
>
> The half-knowledge that I have is often sufficient to see that
> many otherwise nice sources of statistical knowledge are
> dangerously incomplete when it comes to explaining the
> preconditions required for applying a certain technique
> (One example: The extensive NIST handbook at
>  http://www.itl.nist.gov/div898/handbook/
>  fails to mention that the Wilcoxon rank sum test assumes a
>  continuous distribution underlying the sample)
> This is not to speak of how to correctly interpret the results.
>
> My situation is this:
> - I often have a hard time understanding the R documentation
> due to lack of background.
> - I am not in a position to obtain a full background like
> a statistics student would get it.
> - I am very interested in carefully checking/validating my
> application of statistical techniques.
> - I cannot usually get a consulting statistician to help me.
>
> My question:
> Could some of the R gurus maybe agree on a book
> (or very small set of books) with the following properties?:
> - explains typical approaches of statistical analysis
>   (like MASS, but not as condensed)
> - carefully describes preconditions, how to check them,
>   robustness if they are violated, interpretation of results
> - avoids explaining the innards of the techniques
>   (and generally uses the perspective of the computer age)
> - uses terminology that is easily mapped to R
>
> If yes, I would be very interested in seeing this list.
>
> I understand that one book cannot cover it all,
> but maybe there is at least something like "CAS-"
> (Conservative Applied Statistics without S) that
> is of this type?  :-)
>
>   Lutz Prechelt
>
> Prof. Dr. Lutz Prechelt;  prechelt at inf.fu-berlin.de
> Institut für Informatik; Freie Universität Berlin
> Takustr. 9; 14195 Berlin; Germany
> +49 30 838 75115; http://www.inf.fu-berlin.de/inst/ag-se/
>
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