Graph Design for the Eye and Mind

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Graphs have become a fixture of everyday life, used in scientific and business publications, in magazines and newspapers, on television, on billboards, and even on cereal boxes. Nonetheless, surprisingly few graphs communicate effectively, and most graphs fail because they do not take into account the goals, needs, and abilities of the viewers. In raph Design for Eye and Mind, Stephen Kosslyn addresses these problems by presenting eight psychological principles for constructing effective graphs. Each principle is solidly rooted both in the scientific literature on how we perceive and comprehend graphs and in general facts about how our eyes and brains process visual information. Kosslyn then uses these eight psychological principles as the basis for hundreds of specific recommendations that serve as a concrete, step-by-step guide to deciding whether a graph is an appropriate display to use, choosing the correct type of graph for a specific type of data and message, and then constructing graphs that will be understood at a glance. Kosslyn also includes a complete review of the scientific literature on graph perception and comprehension, and appendices that provide a quick tutorial on basic statistics and a checklist for evaluating computer-graphics programs. Graph Design for Eye and Mind is an invaluable reference for anyone who uses visual displays to convey information in the sciences, humanities, and businesses such as finance, marketing, and advertising.
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Editorial Reviews

From the Publisher

"Graphic displays get better and better and become more and more important in the modern information age. Graph Design for Eye and Mind is the best place to learn the art and science of graphic design and comprehension. Stephen Kosslyns fine book is engaging, wise, and exceptionally useful. Read it and you'll become an expert on graphic communication, and you'll learn a lot about how the mind and brain perform one of our species most remarkable skills."--Reid Hastie, Professor of Behavioral Science, University of Chicago

"Finally, a book that connects the art of graph design to the science of visual perception. Stephen Kosslyn, an authority on mental imagery and perception, manages to boil complex research findings down into clear and concrete advice on how to design graphs that illuminate rather than obfuscate."--Keith Holyoak, Distinguished Professor of Psychology, UCLA

"For nearly three decades, Stephen Kosslyn has developed an approach to effective and attractive graph design that rests extensively on scientific evidence. Not only does his treatment provide detailed guidelines for constructing graphs, it explains why these guidelines work, and why numerous pitfalls arise when they're not followed. Students learning to graph data for science, journalism, business, and other graph-intensive activities will benefit significantly from this book. It also offers a reference manual for skilled professionals who need to construct unfamiliar types of graphs on occasion."--Lawrence W. Barsalou, Professor of Psychology, Emory University

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Product Details

  • ISBN-13: 9780195311846
  • Publisher: Oxford University Press, USA
  • Publication date: 5/28/2006
  • Edition description: New Edition
  • Pages: 304
  • Product dimensions: 9.90 (w) x 6.90 (h) x 0.50 (d)

Meet the Author

Stephen M. Kosslyn is the former Chair of the Department of Psychology, currently Dean of Social Science and John Lindsley Professor of Psychology at Harvard University.

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Table of Contents

Table of Contents.
How to use this Book.
Visual Table of Contents.
1. Looking with the Eye and Mind
2. Choosing a Graph Format
3. Creating the Framework, Labels, and Title
4. Creating Pie Graphs, Divided-Bar Graphs, and Visual Tables
5. Creating Bar-Graph Variants
6. Creating Line-Graph Variants and Scatterplots
7. Creating Color, Filling, and Optional Components
8. How People Lie with Graphs
9. Beyond the Graph Appendix 1. Elementary Statistics for Graphs Appendix 2. Analyzing Graphics Programs Appendix 3. Summary of Principles and their Major Corollaries Sources of Data and Figures.

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