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date: 01 July 2022

Abstract and Keywords

This chapter presents issues and complications in statistical inference and uncertainty assessment using public opinion and polling data. It emphasizes the methodologically appropriate treatment of polling results as binomial and multinomial outcomes, and highlights methodological issues with correctly specifying and explaining the margin of error. The chapter also examines the log-ratio transformation of compositional data such as proportions of candidate support as one possible approach for the difficult analysis of such information. The deeply flawed Null Hypothesis Significance Testing (NHST) is discussed, along with common inferential misinterpretations. The relevance of this discussion is illustrated using specific examples of errors from journalistic sources as well as from academic journals focused on measures of public opinion.

Keywords: polling methods, inferences, uncertainty, confidence intervals, margin of error, compositional data, log transformation, null hypothesis, significance testing

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