{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-robust-measure-of-skewness-using-cumulative","title":"A robust measure of skewness using cumulative statistic calculation","arxiv_id":"2209.10699","date":"2022-09-21","proceeding":null,"authors":["Mario Schlemmer"],"abstract":"An important aspect of the shape of a distribution is the level of asymmetry. Strong asymmetries play a role in many ecosystems and are found in the size and reproductive success of individuals. But the standard third moment coefficient of skewness has the drawback that it is very sensitive to outliers, which can lead to incorrect interpretations. A new metric is introduced that is based on calculating the cumulative statistics of the Lorenz curve framework, but it evaluates the asymmetry of the underlying distribution. The standard requirements for skewness measures which the proposed measure satisfies are briefly described and it is compared to the moment-based measure using the lognormal distribution with and without outliers. The results demonstrate that the proposed measure behaves similarly for 'normal' distributions, but is robust(not overly sensitive) if there are outliers.","url_abs":"https://arxiv.org/abs/2209.10699v1","url_pdf":"https://arxiv.org/pdf/2209.10699v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"a-robust-measure-of-skewness-using-cumulative","repo_url":"https://github.com/FT81/cSkew","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}