Título: Errors in election polls
Palestrante: Raphael Nishimura (University of Michigan)

Data:10/03/2021
Horário: 15:30h
Local: Transmissão online

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Resumo: Election polling poses a unique applied statistical challenge as it is one of the very few situations in which the finite population parameters are known at some point briefly after the estimation occurs. In recent years, election polls have been put into question given their performance in major elections, such as the 2016 U.S. Presidential Elections. Understanding what went wrong and finding solutions for their problems is of utmost importance for the survival of this important tool in democracies around the world. Statisticians are generally trained to account for sampling errors in surveys, but there are other sources of error that can have a larger impact on the quality of the survey estimates. The Total Survey Error (TSE) provides a good framework to understand these sources of error and how to address them through design or statistical adjustments. In this presentation, I will review the different sources of errors in election polls from a TSE perspective and present a few case-studies from past election polls to understand how these errors impacted their results.