False precision! Exactly. Even the most sophisticated statistical methods can’t address all bias in these messy data sets. Sometimes we need to focus on the big picture. Trends, rolling averages, triangulating with other studies, viewing everything as an approximation.https://twitter.com/AdamJKucharski/status/1259441470618001409 …
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Plus, exponential dynamics are hard to viscerally understand so models can converge on one thing but that doesn't mean same thing as, say, weather projections but that's how people will interpret model trackers—convergence=stability. Exponential processes can tip over quickly!
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In 2016, people got false comfort from models/odds reported with faux precision (71.4 to 91% chance of Clinton!) and visually presented (the eye overwhelms the fine print). Plus people are used to polls where that would mean a landslide, not odds where it is anything but.
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I’m hopeful that the uncertainty/variability/messiness of the Covid-19 data will lead to a broader discussion and understanding of how to interpret and approach inevitably imperfect data in real time in many fields.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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