Tuesday, December 31, 2013

Where I am on the Drake Equation at the end of 2013

I'm sure you are all familiar with the Drake Equation. It's straightforward: SETI scientist Frank Drake devised it as a way to estimate the number of alien civilizations in our galaxy that we might be able to detect. It's only intended to be a rough guide, and has survived the last 50 odd years because it serves as a good way to divvy up the questions we will need to resolve to answer the bigger question, "Are we alone"?

There are many fine explanations of the terms of the Drake Equation easily available to you, so I won't repeat them. Here are few:

This is how the equation is usually written:

N = R* • fp • ne • fl • fi • fc • L

As we move from left to right across the equation, the terms become less and less well known and harder to estimate, even when we know more. The only thing we're sure of with some of the terms is that none of them are zero, since we are here.

In the last few years, there has been progress. We have gone from knowing just the first term with any kind of accuracy ( a factor of 2 or so), to having solid estimates of the first three terms, and we can now begin to conceive of a research program that would give us an estimate of the fourth term.

Remember, we are only interested in rough numbers here: we just want to know, is N a lot or a little?

So, for 2013, I think we are here:

When is absence of evidence = evidence of absence?

You often hear the old mantra "absence of evidence is not evidence of absence," but I think that this is an oversimplification. The truth is, sometimes it is, and sometimes it isn't. It depends on the experiment, and also how well you understand the implication of the results.

There are times when you can make an excellent case that something is absent because there is no evidence of it. If you are is small, well-lit room, you probably don't need to look under many things to convince any reasonable person that there is no tiger there. In general, you need two things:
  1. You need a solid argument for what sort of evidence you would expect if what you are looking for is there, and how that would be different from the null hypothesis (not there). 
  2. A set of data that tends to falsify the hypothesis, thus advancing the null hypothesis.
We're not talking about "proof" here. I would just as soon we not talk about proof much at all, unless the topic is logic or mathematics. Rather, simply raising or lowering the odds of the null hypothesis, i.e. that the claim in question is not true.