KEY POINTS FROM THIS ARTICLE - We have no idea how much uncertainty exists in pre-election polls. That leads to very complex poll-based forecast model...
http://centerforpolitics.org/crystalball/articles/poll-based-election-forecasts-will-always-struggle-with-uncertainty/
* gave Hillary Clinton a 98% chance of winning * polling error is generally larger than the reported margin of error * when nearly everyone had home telephones * random sampling error * weights * which does result in some biases * coverage error * 78% of the population that relies mostly or completely on cell phones * A handful use “probability” methods * online “nonprobability” polls * vary greatly in quality * likely voters * can easily result in different estimates, depending on the judgment of the decision-makers * potential changes in how we vote * it cannot be accounted for in the data * the model could be adjusted * poll variance would have to be set extremely high * Morris * acknowledged that the model is a work in progress * adjusted * adjustment * will have some data-based ways to adjust for the pandemic * forcing a lot of ad-hoc decisions for election modelers. * Gelman states * My own experience * Michigan * Pennsylvania * Wisconsin * Most people don’t have a solid understanding of how probability works * I tried * most * people * will misunderstand them * will make incorrect assumptions about what they mean * will * filter them through * their own biases * as Morris notes * work hard to communicate model outcomes well * research shows