The Reliability of Polls in the 2020 Election: Understanding Error and Bias

Polls have long been a subject of debate in electoral processes. They are a critical tool for predicting outcomes and shaping political strategies, but their accuracy can be flawed. This article delves into the factors affecting poll reliability and explains why it is crucial to consider these elements when interpreting election results.

The Complexity of Polling Accuracy

Poll results are not infallible due to a variety of factors. Firstly, the design and wording of questions can influence respondents' answers. Additionally, the demographic and geographic representation of the sample can introduce bias. Voter behavior, such as undecided voters, trolling, and non-response bias, also plays a significant role. Even the moment when the poll is conducted can impact results, given that voter opinions may fluctuate over time.

It is important to recognize that while polls can provide valuable insights, they are not a guarantee of electoral outcomes. As the 2016 election demonstrated, a small margin of victory in key swing states can lead to a victory despite a larger national popular vote. In the case of Joe Biden's 2020 race, polls consistently overestimated his support, leading to a narrower margin of victory than initially predicted.

Understanding the Margin of Error

When interpreting poll results, it is crucial to consider the margin of error. This factor represents the level of uncertainty around the poll's findings. For example, a poll showing a 2% lead for one candidate can actually range from 1% lag to 5% lead. This margin of error means that the poll's result is likely to be accurate within this range.

The margin of error is particularly significant in closely contested elections where small changes can lead to different outcomes. Therefore, while a candidate can be leading in a state, it does not necessarily mean they will win. Instead, these polls should be seen as indicative of probabilities rather than certainties.

Delving into Speculative Forecasts

Speculative forecasts, such as those provided by 538, offer a broader context for understanding election outcomes. These models take into account various factors, including historical voting patterns, demographic data, and current polling results. However, even the most sophisticated models cannot account for all variables, and as seen in the 2016 and 2020 elections, there can be unexpected outcomes.

In the 2016 election, 538's final forecast suggested a 71.4% chance of Hillary Clinton winning the election. Despite the poll's accuracy in predicting the popular vote, the outcome was swayed by narrow victories in key swing states. In 2020, the model suggested a more probable outcome, with a forecast margin of 3.5 points. This, combined with a negatively skewed distribution, highlighted the potential for closer results.

The Impact of Voting Efficiency

The context of the election and the efficiency of the voting process can also influence outcomes. Currently, the Republican Party holds an advantage in voting efficiency, meaning there are more scenarios where Trump could win the Electoral College despite losing the popular vote. This implies that a Democratic nominee, such as Kamala Harris, would likely need to win the popular vote by a larger margin to secure a victory.

In summary, while polls are an essential tool for understanding electoral landscapes, they should be interpreted with caution. The margin of error, potential biases, and the broader political landscape all contribute to the uncertainty of election results. Understanding these factors is crucial for accurate analysis and informed decision-making.