Abstract
A strategy for accommodating outlying observations, as well as non-representative, suspect, missing, or otherwise troubling observations, is described. Each unusual observation is decomposed into the sum of two components. One component is the value implied by the trusted observations in the data set. The other component is the unusual part. In this way, the fitting of the data set can then proceed, and, additionally, a numerical value can be ascribed to the unusual part. The method offers not only an antidote for observations with irregular numerical values, which often have the power to contaminate and alter analyses, but also a measure of the magnitudes of the unusual components of those observations. Univariate data and ordered pairs in least-squares fitting are presented as examples.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Date
9-2024
Document Type
Article
Department, Program, or Center
Mathematics and Statistics, School of
College
College of Science
Recommended Citation
Farnsworth, David L., "Analysis of Data Containing Outliers" (2024). Journal of Probability and Statistical Science, 22 (1), 99-105. Accessed from
https://repository.rit.edu/article/2154
Campus
RIT – Main Campus
