John Wilder Tukey

This book serves as an introductory text for exploratory data analysis. It exposes readers and users to a variety of techniques for looking more effectively at data. The emphasis is on general techniques, rather than specific problems.

Exploratory Data Analysis

Introduction and Parts A, B, and C

The Problem of Multiple Comparisons

Ralph Beebe Blackman

An unabridged and corrected republication of Part I and Part II of The measurement of power spectra from the point of view of communications engineering, which originally appeared in the January 1958 and March 1958 issues of volume XXXVII of the Bell system technical journal.

The Measurement of Power Spectra, from the Point of View of Communications Engineering

Frederick Mosteller

Approaching data analysis; Indication and indicators; Displays and summaries for batches; Straightening curves and plots; The practice of re-expression; Need we re-express? Hunting out the real uncertainty; A method of direct assessment; Two-and more-way tables; Robust and resistant measures; Standardizing for comparison; Regression for fitting; Woes of regression coefficients; A class of mechanisms for fitting; Guided regression; Examining regression residuals.

A Second Course in Statistics

Data Analysis and Regression

Kaye Enid Basford

A comprehensive summary of new and existing approaches to analyzing multiresponse data, Graphical Analysis of Multiresponse Data emphasizes graphical procedures. These procedures are then used, in various ways, to analyze, summarize, and present data from a specific, well-known plant breeding trial. These procedures result in overlap plots, their corresponding semigraphical tables, scatter plot matrices, profiles across environments and attributes for individual genotypes and groups of genotypes, and principal components. The interpretation of these displays, as an aid to understanding, is illustrated and discussed. Techniques for choosing expressions for the observed quantities are also emphasized. Graphical Analysis of Multiresponse Data is arranged into three parts: What can usefully be done Consequences for the example Approaches and choices in more detail That structure enables the reader to obtain an overview of what can be found, and to then delve into various aspects more deeply if desired. Statisticians, data analysts, biometricians, plant breeders, behavioral scientists, social scientists, and engineering scientists will find Graphical Analysis of Multiresponse Data offers invaluable assistance. Its details are also of interest to scientists in private firms, government institutions, and research organizations who are concerned with the analysis and interpretation of experimental multiresponse data.

John Wilder Tukey

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