I agree that this statistics problem is a universal issue....Does the problem stem from our expectation that mathematicians/statisticians in the math department will teach the course we want or does it stem from that there is not enough time or skill in our biology courses to teach the statistics and the biology.
Either way, in speaking with our advisement board its clear industry wants their BS degree scientists to have statistical knowledge, and know how to use the various tests properly. The easiest solution would seem to get departments to integrate their courses-lets say a 300 level ecology course and a 300 level statistical design and analysis course. But unfortunately this turns out to be some form of academic fantasy for a variety of reasons. Flame away Charles R. Bomar PhD Professor of Biology University of Wisconsin-Stout Menomonie, WI 54751 [EMAIL PROTECTED] 715-232-2562 -----Original Message----- From: Ecological Society of America: grants, jobs, news [mailto:[EMAIL PROTECTED] On Behalf Of Bill Silvert Sent: Wednesday, November 02, 2005 12:06 AM To: ECOLOG-L@LISTSERV.UMD.EDU Subject: Re: curriculum question At the risk of repeating myself I feel compelled to respond to Ryan Walker's post. Unless the teaching of statistics can be totally changed, I would argue for less statistics, not more. As I have pointed out before, most ecologists can spout ANOVA and t-tests in their sleep, but almost none can do something as basic as adding two numbers (remember my earlier post about adding 100+-3 to 200+-4?). Most statistics courses deal exclusively with linear models to the extent that the majority of books I have surveyed hew to the old line that transformations are for the purpose of linearising data (they should be used to normalise variances). Over all I have seen little of value come out of statistical analyses, which usually just confirm the obvious, but I have some incredibly stupid conclusions drawn from incorrect use of statistics. In balance I think that the value of statistics is not significantly greater than zero, if indeed it is positive at all. Of course this can vary with the subfield. In terrestrial work where sampling tends to be easier and one can lay out quadrats on foot, etc., statistical methods can be very useful. The use of statistical models in the design of agricultural experiments is clearly essential for example. But in areas where data are collected in a more opportunistic way the use of statistics is often a diversion rather than a help. In aquatic ecology, and especially biological oceanography, statistics can be a real nuisance - if anyone ever captured the Loch Ness monster they couldn't publish the news because one is not statistically significant! For a particular example of what I mean, look at fisheries oceanography. The literature of the field is full of schemes for stratified random sampling and negative binomial distributions, but virtually no real ecology. Basically the statistics has edged out the ecology, and it is too hard to do both. Bill Silvert ----- Original Message ----- From: "Walker, Ryan" <[EMAIL PROTECTED]> To: <ECOLOG-L@LISTSERV.UMD.EDU> Sent: Tuesday, November 01, 2005 6:18 PM Subject: Re: curriculum question > Having come from a good undergraduate program (University of Wisconsin - > Stevens Point) and working on a graduate degree at a university with a > somewhat lacking undergraduate program (Texas Tech University), I have > seen both sides of the coin. Regardless of the focus of the program > (Ecology, Wildlife Management, etc.), there is a general need for more > statistics and experimental design. My undergraduate program was more > focused on management and techniques of wildlife ecology and its limited > statistical requirements are still more than other programs. Focusing on > statistics that may be useful for students to know, such as > non-parametrics and multi-variate analyses. I realize that students may > have difficulty grasping some of these more complicated topics, but I feel > it is necessary to expose students to this material. A simple knowledge > of the tools that are available for research would be extremely helpful.
