Wednesday, September 10, 2008

Thinking like a hypothesis

During my first week here, we had a "back to basics" lecture entitled, "Thinking Like a Scientist: How to Formulate a Hypothesis." I wasn't paying much attention, to the above title is what I ended up writing on my page of notes. Sometimes even I wonder what strange malady addles my brain. At least I got some blog fodder out of it.

Of course, the take home message of the whole thing was that a hypothesis isn't scientific if it isn't falsifiable. This could come in any number of forms: The thing you want to prove isn't testable, the way the test is designed automatically gives the assumed result, any outcome results in a confirmation of the hypothesis, etc. This is has to be distinguished from modifying your hypothesis to fit new data. Unfortunately, sometimes modifying the hypothesis can look like bending the data to fit a favored conclusion.

This is one of the things that I find so frustrating about the global warming debate. Not really being versed in the specifics of the science, a lot of what takes place looks to be a case of sticking to a favored conclusion (or in the case of guys like James Hansen, it's more than just appearance). We see things like, "If the glaciers melt, it's global warming, but if they grow in mass, it's also global warming." How could you not reach that conclusion?

Still, I admit the possibility that what we see more of is adaptation of the theories based on expanding data. I don't think this is communicated very well if it's the case. I think what concerns me most is that it doesn't seem to take place enough. There are significant numbers of studies out there which reject the idea that anthropogenic carbon dioxide is going to destroy us all, but it seems like it is more often rejected outright rather than integrated into the existing theories regarding climate science. This wouldn't be so much of a problem if politics weren't so tightly bound to this. When people are proposing plans of action that will restructure society and cost trillions of dollars, it seems like it might be a good idea to take as much information in as possible before you start running with a plan.

Then again, what do I know?

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