• assassin_aragorn@lemmy.world
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    3 months ago

    Recognize that the data may be flawed. Polling is incredibly accurate, but only if you survey a simple random sample. And that is very difficult to do. It introduces a lot of difficulty in getting right answers. Some polling methodologies will try to manipulate the raw data and weight it to try and make it representative, but that introduces a whole host of problems.

    2016 and 2020 under predicted Trump’s popularity for instance, while 2022 under predicted Democrats’ popularity. We don’t know what the situation now.

    Polls are still useful, but you have to treat them with a grain of salt. What tends to be more accurate is changes within the same polling group over time.

      • assassin_aragorn@lemmy.world
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        3 months ago

        You need to look at the actual statistical science. If you find 45% support for something, but there’s a 3% margin of error with a 95% conference interval, then there’s a 95% chance that the true value is anywhere from 42-48%. And that’s with a perfect, simple random sample.

        It has its uses, but you have to be aware of its limitations and caveats.

          • assassin_aragorn@lemmy.world
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            3 months ago

            Are you just arguing for the sake of arguing? I’m saying that even a perfect sample will not necessarily lead to an accurate conclusion, and having a perfect sample is incredibly difficult on top of that.

            Now factor in a major event occurring, and people’s opinions and thoughts being in flux. To properly gauge mood, you need to give people time to process – hence why immediate polling is not helpful.

            You do realize that the person you originally responded to was saying that polls probably aren’t helpful right now, not that polls are universally useless?

            • FiniteBanjo@lemmy.today
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              3 months ago

              Check the context of this thread. Then my words will make more sense and your point reveals itself to be coping to reaffirm unscientific bias.