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Originally Posted by Brupal
If the polls are made up of people who answered a call from an “Unknown Caller” and took 15 minutes to answer the questions, they are hardly representative of anyone except maybe the elderly who were caught between episodes of The Price is Right and Wheel of Fortune and they weren’t out bringing in their bins mere minutes after the collection truck drove away.
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That isn’t how polling works. They are adjusted for demos. They keep calling 18-25 year olds until there is a statistically significant sample or just accept high sample error for those demos.
Polling is reflective of people who answer the phones in each chosen weighted demographic adjusted for likelihood of turnout.
Here’s a good read on polling accuracy from 2020 discussing 2016 failures
https://www.pewresearch.org/short-re...united-states/
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All good polling relies on statistical adjustment called “weighting” to make sure that samples align with the broader population on key characteristics. Historically, public opinion researchers have relied on the ability to adjust their datasets using a core set of demographics to correct imbalances between the survey sample and the population. There is a growing realization among survey researchers that weighting a poll on just a few variables like age, race and sex is insufficient for getting accurate results. Some groups of people – such as older adults and college graduates – are more likely to take surveys, which can lead to errors that are too sizable for a simple three- or four-variable adjustment to work well. Pew Research Center studies in 2016 and 2018 found that adjusting on more variables produces more accurate results.
A number of pollsters take this lesson to heart. The high-caliber Gallup and New York Times/Siena College polls adjust on eight and 10 variables, respectively. Pew Research Center polls adjust on 12 variables. In a perfect world, it wouldn’t be necessary to have that much intervention by the pollster – but the real world of survey research is not perfect.
Failing to adjust for survey respondents’ education level is a disqualifying shortfall in present-day battleground and national polls. For a long time in U.S. politics, education level was not consistently correlated with partisan choice, but that is changing, especially among white voters. As a result, it’s increasingly important for poll samples to accurately reflect the composition of the electorate when it comes to educational attainment. Since people with higher levels of formal education are more likely to participate in surveys and to self-identify as Democrats, the potential exists for polls to overrepresent Democrats. But this problem can easily be corrected through adjustment, or weighting, so the sample matches the population. The need for battleground state polls to adjust for education was among the most important takeaways from the polling misses in 2016.
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