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Data trimming is the process of removing or excluding extreme values, or outliers, from a data set. Data trimming is used for a number of reasons and can be accomplished using various approaches. As social scientists, communication researchers often work with data sets that may require the removal of outliers to strengthen a statistic and accomplish a number of research goals. It is important to understand the impact outliers can have on data and the approaches available to eliminate or censor these extreme values without compromising the data set. This entry provides a detailed explanation of data trimming, including a brief review of alternative terminology, an overview of the most common statistical functions in which data trimming is used, an overview of a method (i.e., ...

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