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The concept of skewness in data distribution and the importance of using the mean or median as a measure of central tendency depending on the presence of outliers. It also discusses the role of standard deviation and interquartile range in measuring spread. Examples of symmetric, skewed left, and skewed right distributions, and provides guidelines for choosing between mean and median based on the shape and presence of outliers.
Typology: Summaries
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UPPER OUTLIERS-^ Pulls Mean higher-^ Pulls St. Dev.higher-^ Pulls Max higher-^ Pulls Range higher LOWER OUTLIERS-^ Pulls Mean lower-^ Pulls St. Dev.higher-^ Pulls Min lower-^ Pulls Range higherMedianQ1Q3IQR
Unaffected by outliersResistant
^ Mean or Median
^ If Symmetric, Unimodal, with no big Outliers– Use the Mean `^ If Skewed or has big Outliers– Use the Median