Hello Howie - (I am one of the few poor souls who actually enjoys reading "long rambles" about imparting good statistical know-how to future scientists :)
I can definitely see your point about the difficulties associated with implementing the Q&K text in introductory courses. As much as I do like it, I have yet to adopt it in my courses. However, I do like the fact that they avoid a 'cookbook' approach, and present quantitative methods within the broader context of conducting science (and thinking about what your are doing!). This is also a strength of Gotelli and Ellison's book, which I also like very much. In fact - although I only require one textbook - I try to emphasize to my students the value of starting their own library, and encourage them to at least take a look at all of the texts which have previously been mentioned. For anyone wanting to pursue a career in science - good resources (and especially stats resources :) are a worthy investment! I will check out the H&H book you mentioned. And I wholeheartedly agree with your aversion to teaching "point and click" approaches to statistical computing!! In addition to reducing error, forcing the use of explicit code creates a reproducable and well-documented history of past analysis (and data management). I have incorporated R into my introductory course, and have had very good success. Once students get over the initial learning curve, they quickly learn to appreciate the power and flexibility of knowing a statistical programming tool. "Introductory Statistics with R" by Peter Dalgaard is a great supplementary text for this purpose. Cheers Stephen On 10/20/06, Howie Neufeld <[EMAIL PROTECTED]> wrote: > > 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 >
