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Used to be data sets were small, chiefly limited by the capacity of the instruments and the time of the investigators or time allocation on the telescopes. This always biased the sample in favor of things with greater apparent brightness, and often by declination (the celestial equivalent of latitude: you can't see the southern polar stars or Magellanic Clouds from northern hemisphere observatories). There are other biases, subtle ones, that enter in as well. If samples are limited to forty stars, and you know there are various not-well-known biases affecting the make-up of the sample, then ... statistics are not much help. The samples are small, and biased in ways you don't really know (or more properly, you are aware a bias exists but you don't know what that bias is doing).

 

Once you got to the state where you could do hundreds of stars (or galaxies) selected from a large population using criteria you know, well, now statistics start becoming useful. But astrophysics didn't enter the "big data" condition until, well, the 1990s.

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That's where the whiskey was spilled?

 

And re: step-mother-in-law, reamed out a couple of 90% blocked blood vessels, two stents, no doubt other stuff that hasn't made it as far down as me. But I was told yesterday afternoon that she might go home today.

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