Outliers detection and treatment: a review.
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....
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Universidad de San Buenaventura
2010
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oai:doaj.org-article:b90136089b3b4d9ab7d150bffa06e9422021-11-25T02:24:04ZOutliers detection and treatment: a review.10.21500/20112084.8442011-20842011-7922https://doaj.org/article/b90136089b3b4d9ab7d150bffa06e9422010-06-01T00:00:00Zhttps://revistas.usb.edu.co/index.php/IJPR/article/view/844https://doaj.org/toc/2011-2084https://doaj.org/toc/2011-7922Outliers 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.Denis CousineauSylvain ChartierUniversidad de San BuenaventuraarticleStatisticsoutlier detectionoutlier treatmentPsychologyBF1-990ENESInternational Journal of Psychological Research, Vol 3, Iss 1 (2010) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN ES |
| topic |
Statistics outlier detection outlier treatment Psychology BF1-990 |
| spellingShingle |
Statistics outlier detection outlier treatment Psychology BF1-990 Denis Cousineau Sylvain Chartier Outliers detection and treatment: a review. |
| description |
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. |
| format |
article |
| author |
Denis Cousineau Sylvain Chartier |
| author_facet |
Denis Cousineau Sylvain Chartier |
| author_sort |
Denis Cousineau |
| title |
Outliers detection and treatment: a review. |
| title_short |
Outliers detection and treatment: a review. |
| title_full |
Outliers detection and treatment: a review. |
| title_fullStr |
Outliers detection and treatment: a review. |
| title_full_unstemmed |
Outliers detection and treatment: a review. |
| title_sort |
outliers detection and treatment: a review. |
| publisher |
Universidad de San Buenaventura |
| publishDate |
2010 |
| url |
https://doaj.org/article/b90136089b3b4d9ab7d150bffa06e942 |
| work_keys_str_mv |
AT deniscousineau outliersdetectionandtreatmentareview AT sylvainchartier outliersdetectionandtreatmentareview |
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