[R-sig-eco] Teaching statistics to ecology undergraduates

[Carsten Dormann]

Dear Graham,

11 hours is short - there's no mistaking. I teach (among other things) a 
6 day stats course for beginners, and find that I need the first 3 days 
to get the student to "think straight". I tried for a couple of years to 
teach "only" GLM, as you suggested. I "waste" one full day of explaining 
what a distribution is, what parameters of distributions are and on what 
ground to suspect data to be derived from a certain distribution. That 
would be at least 5 of your 11 hours. The next half day goes into 
explaining (and running examples) on likelihood and its maximisation. It 
is a good way to start, I find, and eventually students are very 
comfortable using glm rather than aov and friends.
Using only GLM is clear (and Ben Bolker's book sets the right tone, 
albeit at a much too high level for beginners). At the same time, the 
learning curve is VERY steep. 30% of the participants fall by the 
wayside. Is that acceptable? Maybe it is me, not the GLM.

However, I think you have to be very realistic about what you can 
achieve (and I have heard speaking highly of your courses, so I am sure 
you are doing the right things). Giving the students a "feeling" about 
what the idea of a "fit" is and what is behind comparisons of samples is 
rather independent of distributional assumptions and a very general 
point they can take away from a short course.
Also, as you said, visualising the data, getting a feeling for it, is SO 
important, particular when a student has little idea what to expect from 
an experiment/observation.

I my little 6 day course, I spend roughly 2 days on introducing R, 
distributions and (maximum) likelihood (half of this time the 
participants run examples). Another 2 days are devoted to multiple 
regression (going wildly through different distributions to make them 
comfortable with GLM) and issues such as collinearity and model 
selection. Then I throw in a day of design of experiments (randomised 
block, nested, split, survey design, stratification, sample size 
estimation) and run some simple (?) mixed models to illustrate the 
practical problems attached to DOE. The final two days we run largish 
examples (such as Harrell's Titanic data set), touch very superficially 
multivariate methods (PCA, CA and CCA) and end up with some 
miscellaneous issues such as randomisation and bootstrapping.

If I had to reduce it to 11 hours: Unless the students are likely to do 
experiments (which seems to have fallen out of funding), I would ditch 
DOE and focus on GLM plus a few sexy  but tricky examples. I love the 
Titanic study, because you can get the students to identify with the 
passengers. If that leads them to transfer their newly gained knowledge 
to the ecological work is a different question. If you additionally make 
the buy a good book (I always recommend Quinn & Keough, having myself 
been "raised" on Sokal and Rohlf and always hated it, because it never 
addressed my type of non-Gaussian problems) I think they should be set 
up for the next level.

I shall stop now (and prepare some stats course next week), otherwise I 
would also have a word to say about Crawley's approach, which I find 
enchanting and confusing.

Carsten


Graham Smith wrote:
> If, like me, you have a only a few hours (11 hours over 3 years in my 
> case) to try and teach statistics to ecology undergraduates, how do 
> you do it?
>
> Any introductory statistics text seems to assume, more time and more 
> mathematical ability than in practice is available.
>
> Although, I emphasise graphical techniques and the use of confidence 
> intervals, and how these might help understand the ecological process 
> being looked at, I still spend a large chunk of precious time on 
> hypothesis testing.
>
> The more I have been thinking about this, and the more I search for a 
> suitable text book, the more I realise how hopelessly confusing the 
> average text book is, with t-tests, anova, manova, ancova, OLS 
> regression, poission regression, logistic regression GLM etc. Yes I 
> know that all of these may well not appear in the average introductory 
> text.
>
> I have reached the stage  where I am wondering whether I should just 
> teach GLM. This would give the students a single flexible method 
> capable of tackling a wide range of ecological problems. It would 
> also,I think, provide a  better framework for approaching ecological 
> questions than simple hypothesis testing.
>
> I admit, that this email is really just me thinking out loud, but does 
> anyone who teaches statistics to ecologists, or indeed anyone at all 
> really, have any views about how best to spend my 11 hours (which I 
> may be able to increase 13 hours).
>
> I should point out that at the moment I also spend some of this time 
> on good practice in data management, a bit on scientific method, and a 
> bit on the importance of random sampling, but nothing really on 
> experimental design.
>
> Graham
>
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-- 
Dr. Carsten F. Dormann
Department of Computational Landscape Ecology
Helmholtz Centre for Environmental Research UFZ 
Permoserstr. 15
04318 Leipzig
Germany

Tel: ++49(0)341 2351946
Fax: ++49(0)341 2351939
Email: carsten.dormann at ufz.de
internet: http://www.ufz.de/index.php?de=4205