Tools of the Ecological Detective code page

A bit on our philosophy

As ecologists we're used to the messy realities of nature. We think carefully about how to approach a problem, spend inordinate amounts of time researching methods and equipment, and then, when everything breaks, find creative work-arounds to make our experiments work somehow. Yet when it comes to analyzing our messy, complex data we seem to look for the quick way out—canned statistical packages that we don't understand, tortured transformations to shoe-horn our data into a form that we can plug into a statistic we already know, or worst of all, ignoring lots of data because we don't know what to do with it. Well not any more.

We think that as ecologists we should spend as much effort trying to understand our data and answer the questions we first posed as we do collecting the data themselves. We'll need to be creative, we'll need to spend a good deal of mental effort and maybe even some time in the statistical literature to find our way through, but in the end we'll have a much stronger sense of what we found and what we can infer.

Keep in mind

  • If you can't write down your problem, you don't understand it
  • There are almost always other, sometimes more elegant ways to answer a question or get (R) to do something, but who cares about elegance?
  • Most of what you learn in this class, and your graduate education will take place outside of the class room
  • Sharing code makes you a good person
  • Commenting on and improving other people's code makes you an even better person
  • Our goal is to make you "dangerous," not perfect, so don't worry too much about mistakes (but do fix them!)

Other places to find help (especially with R)

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