> I was simply asking if it was verified by showing that weighting by education made the 2016 polls align with reality. To try and answer your technical questi

> I was simply asking if it was verified by showing that weighting by education made the 2016 polls align with reality. To try and answer your technical question: yes and no. I know why you think this would be easy to do. But this is harder to do than you're thinking because the problem with education was both weighting and sampling. So, yes, you can play with the weights and get a corrected result. (That's literally just tautological though -- of course in a parameterized model you can wiggle weights around to give the perfect result when you already know what the result should be...) But, no, that doesn't tell you about what the effect of increasing the sample of these voters would be, and improving sampling is the only real way to get closer to ground truth. So, some pollsters are sampling larger numbers of less educated people and also weighing those votes differently. But no, we can't know what the combined effect of those two things would've been in 2016. Why? because we can wiggle around the weights post hoc but can't go back in time and resample. And the question about correcting without resampling is kinda uninteresting because the fact that you can get the correct result by just wiggling around weights is literally just a mathematical tautology. Hope that helps.