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Understanding Robust and Exploratory Data Analysis

David C. Hoaglin (Editor), Frederick Mosteller (Editor), John W. Tukey (Editor)
ISBN: 978-0-471-38491-5
472 pages
June 2000
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Description

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.
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Table of Contents

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.
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Reviews

"With a dozen chapters aimed at readers of a broad standard deviation of mathematical sophistication, this collection by notables in the field explains...connection of robust techniques and exploratory data analysis..." (SciTech Book News, Vol. 24, No. 4, December 2000)

"As a tribute to the long-lasting impact of this collection of papers, the editors...decided to add Understanding Robust and Exploratory Data Analysis to its Classic Library series...to extend the life of this important work by making it available to future generations of statisticians." (Journal of the American Statistical Association, September 2001)
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