If the earth is the subject, and there is only one earth, is controlled study weakened?

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Dan	If the earth is the subject, and there is only one earth, is controlled study weakened? It seems like much of the argument among non-scientists (like me) boils down to predictive modeling being potentially and wildly unreliable, especially dealing with infinite time frames. Greenhouse gas data from ice cores, for instance, isn't often disputed because it is verifiable. However, the predictions of anthropogenically caused global environmental due to increased greenhouse gases are based on models. There are many models, sometimes with conflicting conclusions, even though they come to generally agreed upon consensus of a warmer planet. The most cogent argument that I (a non-scientist) get from the global warming hoaxers is that we can't really know and the data seems to support them. I'm not looking to discuss global warming here, for the record I'm going with the consensus as it seems the smartest thing to do (I drive a Leaf by the way--that should help categorize me psychographically), what I want to know is how best to defend statistical data when no control group is possible?
	asked on Wednesday, Dec 17, 2014 09:08:06 AM by Dan
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Bo Bennett, PhD 1	Wow, good question. First I would say that we need to take the predictive models on a case by case basis. The level of reliability for each greatly varies. A very important concept in science is known as consilience or convergence of evidence. In our context, this is the idea that multiple models will point to a demonstrable conclusion, even though some valid models will not. This is why deniers (of any scientific fact established from theory) cling to the outliers that confirm their position and ignore consilience. This might be best explained by thinking of a study of coin flips. Let's say that 20 studies were conducted, 19 of which found no statistical difference between heads or tails (what we call having a p-value greater than .05), and one study, out of pure statistical probability, found that heads came up more a statistically significant number of times (p < .05). We can look at this the following ways: 1) focus on the one statistically significant study and claim that coins unfairly land on heads, which is clearly fallacious. 2) Reject the methodology (models) because one came up with completely different results, which is a poor conclusion, but more due to a lack of scientific understanding than fallacious reasoning. Or 3) accept the convergence of evidence pointing to the fact that coin toss results are functionally random, which is by far the best conclusion based on the scientific method and reason. I say functionally because one can get into deep philosophical debates about randomness, which is irrelevant for this example. Also, there are studies that suggest that more than randomness might be at play.
	answered on Wednesday, Dec 17, 2014 09:48:16 AM by Bo Bennett, PhD
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