Perhaps we’re used to coming up with quantitative answers only for numerical data, and don’ t know how to convert from impressions or instincts—even well-informed ones—into those numbers. It feels arbitrary to say 32.5% because it is arbitrary. You can’t break that down into other numbers which explain it. Or, well, you could—you could build a statistical model which incorporated past voting data and trends, and then come up with a figure you could back up with quantifiable evidence—but I’m willing to bet that if you did that, you wouldn’t feel weird about it any more.
For similar reasons, 32.5% seems just too precise a number for the amount of data you’re incorporating into your estimate. You don’t know whether it’s 25% or 40%, a 15% gap, but you’re proposing a mean which adds one significant figure of precision? There’s definitely something wrong with that. I think your discomfort is entirely valid.
Perhaps we’re used to coming up with quantitative answers only for numerical data, and don’ t know how to convert from impressions or instincts—even well-informed ones—into those numbers. It feels arbitrary to say 32.5% because it is arbitrary. You can’t break that down into other numbers which explain it. Or, well, you could—you could build a statistical model which incorporated past voting data and trends, and then come up with a figure you could back up with quantifiable evidence—but I’m willing to bet that if you did that, you wouldn’t feel weird about it any more.
For similar reasons, 32.5% seems just too precise a number for the amount of data you’re incorporating into your estimate. You don’t know whether it’s 25% or 40%, a 15% gap, but you’re proposing a mean which adds one significant figure of precision? There’s definitely something wrong with that. I think your discomfort is entirely valid.