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1 Ιαν 2004 · The goal of this paper is to summarize the various potential causes of extreme scores in a data set (e.g., data recording or entry errors, motivated mis-reporting, sampling errors, and...
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The goal of this paper is to summarize the various potential...
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f outliers in a set of data. We examine the different interests (from rejection of unacceptable contamination, through the accommodation of outliers with reduced influence in robust procedures applied to the whole set of data, to specific identification of outliers as the facets of pri.
14 Ιαν 2013 · There are two types of influential outliers: (a) model fit outliers and (b) prediction outliers. Model fit outliers are data points whose presence alters the fit of a model, and prediction outliers are data points whose presence alters parameter estimates.
30 Ιουν 2010 · Outliers are observations or measures that are suspicious because they are much smaller or much larger than the vast majority of the observations. These observations are problematic because they...
1 Απρ 2013 · The presence of outliers, which are data points that deviate markedly from others, is one of the most enduring and pervasive methodological challenges in organizational science research.
This work demonstrates how to identify outliers in electoral data using informatics methods and suggests that if the data contains significant outliers, the analyst should consider the use of robust statistical techniques.
Definitions. What do we mean by an outlier, exactly? Motivation. Do outliers really matter? Detection. How to detect outliers? Treatment. How to deal with outliers? 2. Important premise. Suggestions shared in this lecture are not a substitute for the protocols that NSOs have in place to ensure data quality.
