So because I am a nerd, today on my walk home I was ruminating about the difference between data and information, and recommendations.
Probably easiest to illustrate with an example. Let's take the problem of, say, restaurants. You want to go to one. How do you pick?
- Data is "here is a list of restaurants, and their locations, and their menus."
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I particularly like this part:
There is a lot of science behind turning data into information, and a bit of art as well -- there are an infinite number of ways one can manipulate data, but not all of them are meaningful...Also, your information is only as good as your data -- how do you know the data you are using is complete and accurate?Because "turning data into information" is a really important part of doing good science! It's why "statistically significant" != "important" and "not statistically significant" != "doesn't matter." Which is something a lot of scientists have a hard time with, in part because statistics tends to be taught SO BADLY. (My MSc stats-for-ag-people course was basically a SAS cookbook, and any actual understanding of statistics anyone learned from it was more or less accidental ( ... )
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And yes to the best innovations seeming obvious after the fact. There's....some kind of something about how people pretend that they were also somehow easy to come up with? Which I think plays into the ongoing stream of "Uber for Popsicles" and whatever else people are doing these days. But I'm not sure how to articulate the chain of logic.
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Humans are odd.
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