Appropriate Critical Values When Testing for a Single Multivariate Outlier by Using the Mahalanobis Distance
Abstract
Kay I. Penny, Appropriate Critical Values When Testing for a Single Multivariate Outlier by Using the Mahalanobis Distance, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 45, No. 1 (1996), pp. 73-81
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A maximum Mahalanobis distance of 13.58 was found, under the critical value of 18.47 for MANOVAs with three dependent variables.
“We found a maximum Mahalanobis distance of 13.58, under the critical value of 18.47 for MANOVAs with three dependent variables (Penny, 1996).”
From Sex Education Among Recent High School Graduates (2025) · cites this paper as Penny, 1996
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- Authors
- Penny, K. I.
- Affiliations
- University of Aberdeen (GB)
- Corresponding author
- Penny, Kay I.
- ORCID
- Penny, Kay I.
- Venue
- Applied Statistics
- Publisher
- JSTOR
- Published
- 1996
- Volume
- 45
- Issue
- 1
- Pages
- 73
- ISSN
- 0035-9254 (ISSN-L)
- OpenAlex
- W165229505
- Cited by
- 214
- References
- 5
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 10 · 2023: 13 · 2022: 14 · 2021: 14 · 2020: 17 · 2019: 8 · 2018: 13 · 2017: 13 · 2016: 13 · 2015: 4 · 2014: 5 · 2013: 8 · 2012: 6
- FWCI
- 4.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Royal Statistical Society Series C (Applied Statistics) (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Keywords
- multivariate outliers, Mahalanobis distance, critical values, outlier detection, multivariate normal distribution
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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