Peter Norvig, Director of Research at Google, provides an FAQ on the election. I haven’t finished reading it, but the analysis appears worth reading.
These same counties went mostly blue in 2004 and 2000. Why? Well, the best answer, says marine biologist Craig McClain, may be an old one, going back before the Civil War, before 1776, before Columbus, back more than 100 million years to the days when the Deep South was under water.
Here’s a good read on the science (and politics) of soda and sugar. For researchers, a key point is:
“If you looked at the secondary endpoints in these studies, said Allison, then yes, each of the studies found one statistically significant result: but they were all for different things and so provided no evidence of consistency that might adduce causality. What was troubling—what the field of obesity research had to avoid—was spinning these secondary endpoints into major findings. You just can’t do this when they weren’t the endpoints you built your study to examine.”
Read Simply Statistics: “The Statistical Method Made Me Lie.”
And Kaiser Fung’s: “A no difference conclusion arises after positive findings are explained away.”
At about 6 minutes into this video, it becomes clear how important statistics are for fundamental science.
I’ve been looking at the data available on cycling accidents in the Bay Area (of which I am a statistic). This data comes from CHP. I’ve learned the hard way to start a data analysis with a small subset of your data (else you sit around waiting for computations to happen), so I’ve started by looking at cycling accidents in Sonoma County.