• @[email protected]
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    6 months ago

    as long as you accept the data

    Ehhhh, data isn’t necessarily sacrosanct. Bad methodology, bad equipment, or bad presentation can lead to biased or misleading data. Hell, every once in a while purely fabricated data slips through the cracks.

    It’s still the best guide we have, and mountains of data from disparate sources should be very suggestive indeed, but science involves being able to question even well-accepted hypotheses, on the slim-but-non-zero chance that all that data was based on some common methodological flaw. If the hypothesis is correct, it’ll stand up to scrutiny.

    Yeah, you’ll get some whackadoos with their thumbs in their navels, but those whackadoos are an important part of the scientific ecosystem; random mutations in scientific evolution which every once in a long while turn out to be useful, if only in getting serious scientists to look at a problem from a new angle. Stagnation’s a bitch.

    • @TropicalDingdong
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      106 months ago

      Yeah but even data sits in the context of a culture that sets up the experiment and sample design to get the data.

      And most data is expensive AF. I did a recent calculation to figure out how much it cost us to get around 3000 samples of a particular data type. The answer was in the tens of millions, over decades,.and multiple careers. and it’s still not remotely enough to capture the variation we know exists.

      I wrote.om this the other day, but it’s something the op.is alluding to, but maybe didn’t quite hit. Every scientific statement of fact must have some epsilon of uncertainty associated with it, and this includes our data. Did they GPS unit lie to you about where you where? was there some other source of interference with the instrument? How much confidence do you have in the voltage it was actually detecting? How about the physical principles the instrument is based on? How confident are we in those?

      It’s epsilons the way down. But that’s actually fine And important. The facts and the data need to be able to be rejected when they are wrong. If we haven’t left even a tiny hole of uncertainty we can escape out of, it’s left the realm of science and has become dogma