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Closely related to nonparametric methods, robust statistical methods are not unduly affected by data outliers or other small departures from model assumptions. This book presents a comprehensive overview of methodology for robust and nonparametric statistics. It covers both methods in parallel to demonstrate their relative strengths and weaknesses. Using examples to illustrate the methods, the text emphasizes applications in the fields of biomedical science, bioinformatics, finance, and engineering. The authors provide exercises in the text.