The Elements of Graphing Data

How to Order

Principles of graph construction and the visual communication of data. Visualization methods. The principles and methods are supported by a rigorous, scientific discussion of graphical perception, the visual decoding of information from data displays. Prerequisites: None.

Quotes from Reviewers

J. Lodge, Atmospheric Environment:
``certain kinds of tendency toward bad graphics could be cured if as many authors as possible would not just read, but, in the words of the Anglican Prayer Book, `learn, mark, and inwardly digest' this volume.''

R. A. Thisted, Computing Reviews:
``This is an admirable book. It is clearly written and intellectually engaging.''

J. C. Thompson, Jr., Cornell Veterinarian:
``a wealth of examples which make it easy to read and understand.''

J. M. Olson, The American Cartographer:
``An excellent stimulus for deeper thinking about display techniques ... ''

B. D. Spurr, Biometrics:
``There is so much to learn from this book that it took me considerable time to get through it despite it not being a long book.''

P. McPhie, Analytical Biochemistry:
``The quality of the scientific literature would greatly increase if the book were studied by all authors (actual and potential), referees, and editors.''

L. S. Nelson, Journal of Quality Technology:
``It is hard to imagine anyone reading this book and not getting some good ideas to put immediately into practice.''

College and Research Libraries:
``This book is a gem. Buy it, read it and urge everyone you know whose job it is to convert raw data to meaningful information to do the same.''

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T. S. Hills, Meteorological Magazine:
``Ideally, everyone interested in getting the most out of their data or presenting data clearly and concisely should have a copy handy.''

Preface

This book is about visualizing data in science and technology. It contains graphical methods and principles that are powerful tools for showing the structure of data. The material is relevant for data analysis, when the analyst wants to study data, and for data communication when the analyst wants to communicate data to others.

When a graph is made, quantitative and categorical information is encoded by a display method. Then the information is visually decoded. This visual perception is a vital link. No matter how clever the choice of the information, and no matter how technologically impressive the encoding, a visualization fails if the decoding fails. Some display methods lead to efficient, accurate decoding, and others lead to inefficient, inaccurate decoding. It is only through scientific study of visual perception that informed judgments can be made about display methods. The display methods of Elements rest on a foundation of scientific enquiry.

Except for one small section, there is nothing in this book about computer graphics. The basic ideas, the methods, and the principles of the book transcend the computing environment used to implement them. While graphics technology is moving along at a rapid pace, the human visual system has remained the same.

The prerequisites for understanding the book are minimal. A few topics require a knowledge of the elementary concepts of probability and statistical science, but these topics can be skipped without affecting comprehension of the remainder of the book.

The book Visualizing Data is a companion volume It focuses on graphical methods, the topic of Chapter 3 of this book; it presents far more methods than covered here and is more advanced, requiring a greater knowledge of statistics. But Visualizing Data does not delve into graphical perception, and takes Elements as a starting point.

Elements was meant to be read from the beginning and to be enjoyed. However, it is possible to read here and there. Winding its way through the book is a summary of the material: the figures and their legends. Reading this summary can help readers direct themselves to specific items.

The graphs in this book are communicating information about fascinating subjects, and I have not hesitated to describe the subjects in some detail when needed. In many cases some knowledge of the subject is required to understand the purpose of a graphical analysis or why a graph is not doing what was intended or what a new graphical method can show us about data. I hope the reader will share with me the excitement of experiencing the increased insight that graphical data display brings us about these subjects.