Outliers detection and treatment: a review.
Denis Cousineau
Département de psychologie, Université de Montréal, C.P. 6128, succ. Centre-ville, Montréal, Québec
Sylvain Chartier
University of Ottawa


outlier detection
outlier treatment

How to Cite

Cousineau, D., & Chartier, S. (2010). Outliers detection and treatment: a review. International Journal of Psychological Research, 3(1), 58-67. https://doi.org/10.21500/20112084.844


Outliers are observations or measures that are suspicious because they are much smaller or much larger than the vast majority of the observations. These observations are problematic because they may not be caused by the mental process under scrutiny or may not reflect the ability under examination. The problem is that a few outliers is sometimes enough to distort the group results (by altering the mean performance, by increasing variability, etc.). In this paper, various techniques aimed at detecting potential outliers are reviewed. These techniques are subdivided into two classes, the ones regarding univariate data and those addressing multivariate data. Within these two classes, we consider the cases where the population distribution is known to be normal, the population is not normal but known, or the population is unknown. Recommendations will be put forward in each case.


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