Exploring Data Tables, Trends, and Shapes

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area."
—Technometrics

"This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously."
—The Statistician

This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.Content:
Chapter 1 Theories of Data Analysis: From Magical Thinking Through Classical Statistics (pages 1–36): Persi Diaconis
Chapter 2 Fitting by Organized Comparisons: The Square Combining Table (pages 37–66): Katherine Godfrey
Chapter 3 Resistant Nonadditive Fits for Two?Way Tables (pages 67–124): John D. Emerson and George Y. Wong
Chapter 4 Three?Way Analyses (pages 125–188): Nancy Romanowicz Cook
Chapter 5 Identifying Extreme Cells in a Sizable Contingency Table: Probabilistic and Exploratory Approaches (pages 189–224): Frederick Mosteller and Anita Parunak
Chapter 6 Fitting Straight Lines by Eye (pages 225–239): Frederick Mosteller, Andrew F. Siegel, Edward Trapido and Cleo Youtz
Chapter 7 Resistant Multiple Regression, One Variable at a Time (pages 241–279): John D. Emerson and David C. Hoaglin
Chapter 8 Robust Regression (pages 281–343): Guoying Li
Chapter 9 Checking the Shape of Discrete Distributions (pages 345–416): David C. Hoaglin and John W. Tukey
Chapter 10 Using Quantiles to Study Shape (pages 417–460): David C. Hoaglin
Chapter 11 Summarizing Shape Numerically: The g?and?h Distributions (pages 461–513): David C. Hoaglin