Generally however those concerned, after the fact, about the rigor of their statistics (or lack thereof) are not reporting naturalistic observations but attempting to hammer their round data pegs into the square holes of already established theory.
If your concern is naturalistic observation, you don't have to have too much concern about whether or not you've properly articulated (or understand) the underlying statistical model you're testing. Ned Dochtermann -----Original Message----- From: Ecological Society of America: grants, jobs, news [mailto:[EMAIL PROTECTED] On Behalf Of Bill Silvert Sent: Thursday, March 09, 2006 4:29 AM To: [email protected] Subject: Re: "Hamerstrom science" (deliberate non-use of statistical analysis) Although Mike doesn't use the term, this is a nicely put statement of the message that modellers have been trying to get across for eons, that one should model a system before doing the field work in order to design the experiments optimally. Too often I have had people approach me with masses of data, but without the critical information that is needed to understand the system. On the other hand, if one only carries out field work to test pre-existing ideas, how can you discover anything new? One of the greatest scientific events of the past century was the discovery of ecosystems based on chemosynthesis rather than photosynthesis, but this was just the result of sending down a ROV and had nothing to do with hypothesis testing. And Darwin did not set out to test evolution, he joined the Beagle as a field naturalist and developed his theory from his observations. I suspect that these and other major scientific developments would not pass the rigorous tests of "correct science". Bill Silvert ----- Original Message ----- From: "Michael Sears" <[EMAIL PROTECTED]> To: <[email protected]> Sent: Thursday, March 09, 2006 1:00 AM Subject: Re: "Hamerstrom science" (deliberate non-use of statistical analysis) > If you can design an elegant experiment that only requires a t-test for > its > analysis, that is admirable. But the simple truth of the matter, in my > experience, is that many folks don't take the time to design a good > experiment, > often collect data with disregard to any theory, and simply collect what > is easy > or is the data that everyone else collects, hoping in the end that somehow > through mathemagic, they can make something out of their efforts. To > paraphrase > Burnham and Anderson, 90% of our time should be spent thinking and only > 10% > doing. I'd suggest folks be aware of theory and design experiments with > regard > to it, such that the design and analysis are set BEFORE the data are > collected. > Often, but not always, if that is done, an overly complex analysis may not > be > necessary...but some complicated hypotheses do require complex analyses. > This is > the nature of good science. > > > Mike Sears
