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Target-Centric Astronomy

Astronomy has a kindred cousin, a cool one who wears his sunglasses at night: intelligence analysis. I don’t just mean reconnaissance satellites, either; the process of astronomy, that of observing and drawing conclusions, is possibly the most similar of all the sciences to the process of intelligence gathering. Both fields deal with low signal-to-noise regimes that are based primarily on observation rather than experimentation. Both fields must continually account for errors and biases that could easily lead to false or falsely credited conclusions. And thus it behooves us as astronomers to learn from our cousins on the other side of the fence, who may not have been in the business quite as long or have quite as much ground to cover, but who certainly have a lot more pressure to produce results. That’s why today I’m going to be talking about Robert M. Clark’s key textbook Intelligence Analysis: A Target-Centric Approach, and what lessons it holds for you as a professional scientist. Continue reading

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Wishy-Washy Water World

When we dream of other worlds, there is one thing that drives our fantasies of life above all else: water.  Most organisms on Earth rely on this molecule for survival.  Although we might imagine life forms that do not require water, planets with water are the most obvious places to search for life—or at least … Continue reading

Astrostatistics: How to fit a model to data

Why does the fit above look so crappy? Probably because of those pesky outliers! But before you get rid of them, see what David Hogg has to say about alternative methods of fitting models which are not only more robust, but may change your mind about every fit you do from now on. Continue reading

Biases in Astronomy: Is the M-sigma relation an upper limit?

The word “bias” shows up all the time in astronomy. What exactly does it mean? Also, how a recent study tackles the argument that the M-sigma relation may be biased. Continue reading

Inelastic Dark Matter Ruled Out?

The new XENON100 results do not support models of inelastic dark matter used to reconcile the DAMA modulation signal with null detections from other experiments. But what’s DAMA and “inelastic dark matter”? Continue reading

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