Description
This handbook introduces readers to regression diagnostic analysis, a technique used in applied statistics. It covers methods for detecting outliers and inadequate models, transforming variables in an equation, and advanced topics such as generalized linear models. The book is heavily illustrated with examples and presents up-to-date research findings.
This handbook provides a detailed, down-to-earth introduction to regression diagnostic analysis, a technique of growing importance for work in applied statistics. Heavily illustrated, with numerous examples to illuminate the discussion, this timely volume outlines methods for regression models, stressing detection of outliers and inadequate models; describes the transformation of variables in an equation, particularly the response; and considers such advanced topics as generalized linear models. A useful guide that combines lucid explanations with up-to-date research findings.
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