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Outliers in Statistical Data
Abstract
An updated edition of this standard reference work on outliers. Includes new areas of study such as outliers in direction data as well as developments in fields such as discordancy tests for univariate and multivariate samples. Re-organized to provide a more logical approach. Provides relevant illustration and tabulation as well as suggestions for further research.
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Citations
Cited by
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
LOF: identifying density-based local outliers
Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335388 · Cited by 5,207
A Survey of Outlier Detection Methodologies
Hodge, V., & Austin, J. (2004) · Artificial Intelligence Review · doi:10.1007/s10462-004-4304-y · Cited by 3,596
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162
Ego depletion and the strength model of self-control: a meta-analysis
Hagger, M. S., Wood, C., Stiff, C., & Chatzisarantis, N. L. D. (2010) · Psychological Bulletin · doi:10.1037/a0019486 · Cited by 2,265
Metadata
- Authors
- Barnett, V., Lewis, T., & Abeles, F.
- Venue
- Physics Today
- Publisher
- AIP Publishing
- Published
- 1979-09-01
- Volume
- 32
- Issue
- 9
- Pages
- 73-74
- ISSN
- 0031-9228 (ISSN-L)
- 1945-0699
- OpenAlex
- W1970655212
- Cited by
- 2,824
- References
- 0
- FWCI
- 28.05
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: Outliers in Statistical Data. https://app.cochat.ai/papers/10.1063/1.2995737
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- Barnett, V., Lewis, T., & Abeles, F. (1979). Outliers in Statistical Data. Physics Today. https://doi.org/10.1063/1.2995737
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
