Dear All - the thread about which statistical text to use is interesting
to read, and reflects, I think, the depth and breadth of statistical
sophistication among us ecologists. Those of us with a smattering to
moderate amount would probably prefer a more introductory book for our
incoming graduate students, while those with a lot of training in
statistics would prefer a higher powered book.
For years I used Zar - it does have depth and breadth, and plenty of
examples worked out. It's a great reference book too. Others seem to
prefer Quinn and Keough. And I'm sure there are yet others who have
their own favorite texts. Based on my sampling, I think the only true
conclusion is that medical statisticians write the absolutely worst
texts and ecologists the best ones!
However, this year I switched texts to one by Hampton and Havel
(H&H) because I realized that in my intro biometrics course (that's what
we call it here historically) I never got to at least half of the
chapters in Zar, not to mention that the Zar book is expensive. Much
the same material I covered in past years is included in the H&H book.
But because its paperback, it has a greatly reduced price (~$25). It's
also geared for those students with essentially no a priori background
in statistics, and my students like it so far.
I found the Quinn and Keough book way too advanced for the
introductory student. From a pedagogical point of view, I thought it
was poorly developed. It had its moments, but as a teaching tool for
students just starting out, it would have been way to much for my
students. It too contains much more material than I could ever cover in
my intro course.
Not wanting my students to have too much disposable income, I
supplement the H&H text with Gotelli and Ellison's new Primer on
Ecological Statistics, because I like their philosophy and approach to
statistics. However, they provide no work study problems, but again,
and as Aaron Ellison has told me, that was not their goal. But their
discussions of why we do statistics, the history involved, and their
section on experimental design are all highly readable, so I assign this
as an auxiliary text for them. I especially like their discussion of
what Bayesian statistics are, and how they can be used. That is not
something most of even mention in intro courses.
Finally, we conduct a SAS lab each week. Yes, I'm one of the dodos
of the statistical world that still finds SAS programming useful, and so
I inflict this on my students (If I had to do it.....! - no that's not
the reason!). For this we use Cody and Smith's "Applied Statistics and
the SAS Programming Language". I'm sure there are those who find this
type of training anachronistic, but simply using point and click
programs often leads to errors in experimental design and then analysis,
which are less likely if you are writing the programming yourself. By
the end of their first semester, they can move on to point and click
programs, so they end up with several skills here.
The main problem we have at Appalachian State is a follow-up
experimental design course for our graduate students. I would be most
happy if someone who is teaching a second semester course in this area
would send me their syllabus. We want to set up such a course here, and
I would appreciate feedback as to what we should include in such a course.
Thanks for listening to this long ramble.
Howie Neufeld
--
Dr. Howard S. Neufeld, Professor
Department of Biology
572 Rivers Street
Appalachian State University
Boone, NC 28608
email: [EMAIL PROTECTED]
departmental webpage: http://www.biology.appstate.edu/faculty/neufeldhs.htm
personal webpage: http://www.appstate.edu/~neufeldhs/index.html
Tel: 828-262-2683
Fax: 828-262-2127
