BOOK

Identification of Outliers

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Identification of Outliers by David M. Hawkins (1980) presents a comprehensive statistical framework for detecting observations that deviate from the expected structure of a dataset. The book develops both theoretical foundations and practical methods for identifying outliers in univariate and multivariate settings. It emphasizes the impact of outliers on statistical inference, including parameter estimation, regression analysis, and model reliability.

Hawkins introduces classical detection techniques alongside robust statistical approaches designed to reduce the influence of extreme or abnormal observations. A significant contribution of the work is its treatment of multivariate outliers, where relationships among variables are considered rather than examining each variable separately. The book also discusses the concept of influence, showing how certain data points can disproportionately affect statistical conclusions.

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Availability

Detail Information

Series Title

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Call Number

519.5 H393

Publisher

: SPRINGER., 2014

Collation

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Language

English

ISBN/ISSN

‎ 9401539960

Classification

519.5

Content Type

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Media Type

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Carrier Type

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Edition

1980th

Subject(s)

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Specific Detail Info

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Statement of Responsibility

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Other version/related

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