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Braining, slowly
Oct. 25th, 2016 12:07 pmWe're back on deck with the circadian experiment.
One of the most challenging aspects, for me, is when I have these long evenings that I can't really put to effective use. I tried to work on some statistical analyses last night, but I really needed to look stuff up in Zar, which was at home. So I just ate too many biscotti instead.
I have this other massive stats book at work called Applied Linear Statistical Models (which I will call NKNW after its authors), but it's ever-so-slightly more mathematical and less pragmatic than Biostatistical Analysis (aka Zar). So when I need to look up something like how to calculate statistical power, NKNW doesn't actually help.
Nor does the internet, because as we all know the internet isn't a vetted source, and you'll find about 12 different sources with 12 different styles of calculations. In addition, for a lot of stats stuff it's helpful to learn a consistent set of variables and calculations because there's a hell of a lot of sloppy work out there and it's easy to get stuck in a swamp of incomprehension because someone defines things in a slightly different fashion. And that's how "Data Science" got invented.
Today, however, I have Zar again, so maybe I can fwump myself over this hurdle and on to the next thing (job applications again).
One of the most challenging aspects, for me, is when I have these long evenings that I can't really put to effective use. I tried to work on some statistical analyses last night, but I really needed to look stuff up in Zar, which was at home. So I just ate too many biscotti instead.
I have this other massive stats book at work called Applied Linear Statistical Models (which I will call NKNW after its authors), but it's ever-so-slightly more mathematical and less pragmatic than Biostatistical Analysis (aka Zar). So when I need to look up something like how to calculate statistical power, NKNW doesn't actually help.
Nor does the internet, because as we all know the internet isn't a vetted source, and you'll find about 12 different sources with 12 different styles of calculations. In addition, for a lot of stats stuff it's helpful to learn a consistent set of variables and calculations because there's a hell of a lot of sloppy work out there and it's easy to get stuck in a swamp of incomprehension because someone defines things in a slightly different fashion. And that's how "Data Science" got invented.
Today, however, I have Zar again, so maybe I can fwump myself over this hurdle and on to the next thing (job applications again).
