Understanding Robust and Exploratory Data Analysis

Häftad, Engelska, 2000

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Beskrivning

Originally published in hardcover in 1982, this book is now offered in a Wiley Classics Library edition. A contributed volume, edited by some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use exploratory data analysis and robust and resistant methods in statistical practice.

Produktinformation

Utgivningsdatum:2000-06-14
Mått:152 x 231 x 29 mm
Vikt:670 g
Format:Häftad
Språk:Engelska
Serie:Wiley Classics Library
Antal sidor:480
Förlag:John Wiley & Sons Inc
ISBN:9780471384915

Utforska kategorier

Matematisk statistik inom Naturvetenskap och teknik

Mer om författaren

DAVID C. HOAGLIN, PhD, is a Fellow of the American Statistical Association. FREDERICK MOSTELLER, PhD, has been the recipient of several honorary degrees and is a former President of the American Statistical Association.

Recensioner i media

"With a dozen chapters aimed at readers of a broad standarddeviation of mathematical sophistication, this collection bynotables in the field explains...connection of robust techniquesand exploratory data analysis..." (SciTech Book News, Vol. 24, No.4, December 2000) "As a tribute to the long-lasting impact of this collection ofpapers, the editors...decided to add Understanding Robust andExploratory Data Analysis to its Classic Library series...to extendthe life of this important work by making it available to futuregenerations of statisticians." (Journal of the American StatisticalAssociation, September 2001)

Innehållsförteckning

Stem-and-Leaf Displays (J. Emerson & D. Hoaglin). Letter Values: A Set of Selected Order Statistics (D.Hoaglin). Boxplots and Batch Comparison (J. Emerson & J. Strenio). Transforming Data (J. Emerson & M. Stoto). Resistant Lines for y Versus x (J. Emerson & D. Hoaglin). Analysis of Two-Way Tables by Medians (J. Emerson & D.Hoaglin). Examining Residuals (C. Goodall). Mathematical Aspects of Transformation (J. Emerson). Introduction to More Refined Estimators (D. Hoaglin, et al.). Comparing Location Estimators: Trimmed Means, Medians, and Trimean(J. Rosenberger & M. Gasko). M-Estimators of Location: An Outline of the Theory (C.Goodall). Robust Scale Estimators and Confidence Intervals for Location (B.Iglewicz). Index.