Are our data symmetric?

Research output: Contribution to journalShort surveypeer-review

9 Scopus citations

Abstract

Skewness indicates a lack of symmetry in a distribution. Knowing the symmetry of the underlying data is essential for parametric analysis, fitting distributions or doing transformations to the data. The coefficient of skewness is the commonly used measure to identify a lack of symmetry in the underlying data, although graphical procedures can also be effective. We discuss three different methods to assess skewness: traditional coefficient of skewness index, skewness index based on the L-moments discussed by Hosking and the asymptotic test of symmetry developed by Randles et al. With this work, we provide easy-to-implement S-PLUS® functions as well as discuss the advantages and shortcomings of each technique.

Original languageEnglish (US)
Pages (from-to)505-513
Number of pages9
JournalStatistical Methods in Medical Research
Volume12
Issue number6
DOIs
StatePublished - Dec 1 2003

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

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