Univariate Outliers: A Conceptual Overview for the Nurse Researcher

Abstract

The presence of statistical outliers is a shared concern in research. If ignored or improperly handled, outliers have the potential to distort the estimate of the parameter of interest and thus compromise the generalizability of research findings. A variety of statistical techniques are available to assist researchers with the identification and management of outlier cases. The purpose of this paper is to provide a conceptual overview of univariate outliers with special focus on common techniques used to detect and manage univariate outliers. Specifically, this paper discusses the use of histograms, boxplots, interquartile range, and z-score analysis as common univariate outlier identification techniques. The paper also discusses the outlier management techniques of deletion, substitution, and transformation.