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Apra Lipi (Author), Kishan Kumar (Author), Soubhik Chakraborty (Author)Series: Mathematics Research Developments
BISAC: MAT000000; MAT029050
DOI: https://doi.org/10.52305/HNKB4808
This brief monograph, in the broadest terms, reviews some of the techniques for outlier detection and analysis. In addition, the effect of the presence of outliers on the statistical parameters such as higher-order moments, quartiles, deciles, percentiles, skewness, and kurtosis, etc. of the distribution are studied. It also discusses the masking and swamping effect of outliers and some primitive methods of detecting these behaviors. Furthermore, some methods of detecting outliers in multivariate data using the clustering algorithm approach are also discussed.
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Preface
About the Authors
Chapter 1. Introduction
Chapter 2. Outliers: To Discard or Not to Discard
Chapter 3. Methods of Outlier Detection
Chapter 4. Challenges and Impacts of Outlier Detection
Chapter 5. Statistical Tests for Outlier Detection and Outlier Treatment
Chapter 6. Other Statistical Methods
Chapter 7. Outliers in the Real World
Chapter 8. Outlier Detection in Time Series Data
Chapter 9. Discussion and Conclusion
References
Index
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