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Submitted ⁨⁨1⁩ ⁨year⁩ ago⁩ by ⁨fossilesque@mander.xyz⁩ to ⁨science_memes@mander.xyz⁩

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  • AnarchistArtificer@slrpnk.net ⁨1⁩ ⁨year⁩ ago

    As a biochemist who is better at stats than the average biochemist (which is concerning, because I’m not that great), I greatly appreciate statisticians telling us off when we’re fools.

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    • Shiggles@sh.itjust.works ⁨1⁩ ⁨year⁩ ago

      The second most useful thing I learned from statistics courses was the statistics. The first was just how terrible most people are in their application.

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  • Zehzin@lemmy.world ⁨1⁩ ⁨year⁩ ago

    Statistitians are good people, though I need more data points to say anything conclusive

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    • marcos@lemmy.world ⁨1⁩ ⁨year⁩ ago

      Just to point out, but you need to make sure your data is unbiased much more than you need a lot of points.

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    • merari42@lemmy.world ⁨1⁩ ⁨year⁩ ago

      Can you at least say how your prior belief distribution has shifted or been reaffirmed given the observed data points?

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      • Zehzin@lemmy.world ⁨1⁩ ⁨year⁩ ago

        That would be pretty Bayesed

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  • kender242@lemmy.world ⁨1⁩ ⁨year⁩ ago

    “Trust in numbers” was an eye opening book I had to read for a university course.

    https://press.princeton.edu/books/paperback/9780691208411/trust-in-numbers

    The idea that “It’s difficult to get numbers to tell you the truth” despite how people tend to think hard data is not falsifiable - was my main take.

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    • undercrust@lemmy.ca ⁨1⁩ ⁨year⁩ ago

      For a really good riff on this same idea, I like “How to Lie With Statistics” by Darrell Huff, and it’s all illustrated!

      Great, easy to understand breakdown of how statistics can be manipulated.

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      • DragonTypeWyvern@literature.cafe ⁨1⁩ ⁨year⁩ ago

        I honestly think that book should be required high school reading.

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