Effective Data Visualization: The Right Chart for the Right Data (2nd Edition)

Description

Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate their data findings. This comprehensive how-to guide functions as a set of blueprints—supported by both research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. Delivered in Evergreen’s humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for building the chosen graph in Excel.

Now in full color with new examples throughout, the Second Edition includes a revamped chapter on qualitative data, nine new quantitative graph types, new shortcuts in Excel, and an entirely new chapter on Sharing Your Data With the World, which provides advice on using dashboards.

New from Stephanie Evergreen! The Data Visualization Sketchbook provides advice on getting started with sketching and offers tips, guidance, and completed sample sketches for a number of reporting formats. Bundle Effective Data Visualization, 2e, and The Data Visualization Sketchbook, using ISBN 978-1-5443-7178-8!

Key Features

• The “Chart Chooser” one-page diagram located on the inside front cover serves as a quick reference for readers to choose the right chart for their data.
• Step-by-step instructions with screenshots for data visualization development in Excel demonstrate exactly how to create graphs with impact.
• An engaging, logical narrative features the kinds of stories that can be told about a data set, relying on common research questions and presentation intentions.
•  “Ninja ratings” for graph types indicate their difficulty level in Excel.
• Success stories showcase how creating effective data visualization can be a way to go beyond producing charts and tables and create organizational culture change.

New to this Edition

• Every image is now in full color, making it easier to match your screen to the book’s screenshots for easy, impactful data viz.
• Nine new quantitative graph types in this edition include overlapping bars, vertical dumbbell dot plots, waffle charts, pictographs, bump charts, connected scatterplots, waterfalls, tile maps, and combination charts with target lines.
• This edition introduces a qualitative chart chooser on the inside back cover and the largest compendium of qualitative visualization options ever published, from journey maps and histomaps to spectrum displays.
• Additional peer-reviewed research on human perception, cognition, psychology, and data visualization supports chart recommendations and gives readers more confidence when trying out new graph types.
• Strategies for building a culture of effective data visualization throughout your organization are covered.
• A new chapter on making interactive dashboards in Excel is included in this edition.

Table of Contents

1. PREFACE
2. ACKNOWLEDGMENTS
3. ABOUT THE AUTHOR
4. Chapter 1. Our Backbone: Why We Visualize
   1. Why We Visualize
   2. When Visualization Is Harmful
   3. Which Chart Type Is Best?
   4. Tell a Story With Data
   5. How to Use This Book
   6. Exercises
   7. Resources
   8. References
5. Chapter 2. When a Single Number Is Important: Showing Mean, Frequency, and Measures of Variability
   1. What Stories Can Be Told With a Single Number?
   2. How Can I Visualize a Single Number?
   3. How Can I Show Measures of Variability?
   4. Exercises
   5. Resources
   6. References
6. Chapter 3. How Two or More Numbers Are Alike or Different: Visualizing Comparisons
   1. What Stories Can Be Told About How Two or More Numbers Are Alike or Different?
   2. How Can I Visualize How Two or More Numbers Are Alike or Different?
   3. Exercises
   4. Resources
   5. References
7. Chapter 4. How We Are Better or Worse Than a Benchmark: Displaying Relative Performance
   1. What Stories Can Be Told About How We Are Better or Worse Than a Benchmark?
   2. How Can I Visualize How We Are Better or Worse Than a Benchmark?
   3. Exercises
   4. Resources
   5. References
8. Chapter 5. What the Survey Says: Showing Likert, Ranking, Check-All-That-Apply, and More
   1. What Stories Can Be Told About What the Survey Says?
   2. How Can I Visualize What the Survey Says?
   3. Ranking
   4. Branching
   5. Visualizing Not Applicable or Missing Data
   6. Exercises
   7. Resources
   8. References
9. Chapter 6. When There Are Parts of a Whole: Visualizing Beyond the Pie Chart
   1. What Stories Can Be Told When There Are Parts of a Whole?
   2. How Can I Visualize the Parts of a Whole?
   3. Exercises
   4. Resources
   5. References
10. Chapter 7. How This Thing Changes When That Thing Does: Communicating Correlation and Regression
    1. What Stories Can Be Told About How This Thing Changes When That Thing Does?
    2. How Can I Visualize How This Thing Changes When That Thing Does?
    3. Exercises
    4. Resources
    5. References
11. Chapter 8. When the Words Have the Meaning: Visualizing Qualitative Data
    1. What Stories Can Be Told When the Words Have the Meaning?
    2. How Can I Visualize When the Words Have the Meaning?
    3. Pure Qualitative: Highlight a Word
    4. Pure Qualitative: Thematic Analysis
    5. Some Quantification: Highlight a Word
    6. Some Quantification: Thematic Analysis
    7. Exercises
    8. Resources
    9. References
12. Chapter 9. How Things Changed Over Time: Depicting Trends
    1. What Stories Can Be Told About How Things Changed Over Time?
    2. How Can I Visualize How Things Changed Over Time?
    3. Exercises
    4. Resources
    5. References
13. Chapter 10. Reporting Out: Sharing Your Data With the World
    1. Static Visuals
    2. Interactive Dashboards
    3. Exercises
    4. Resources
    5. References
14. Chapter 11. It’s About More Than the Buttons
    1. Dot Plots Generate Healthcare Pioneers
    2. Clearly Labeled Line Graphs Streamline Decisions at a Fortune 500
    3. Diverging Stacked Bars Make for Community Leaders in the Midwest
    4. Icons Support Informed Policymaking
    5. Building a Culture of Effective Data Visualization
    6. Exercises
    7. Resources
    8. References
    9. INDEX

Author Biography

Dr. Stephanie D. H. Evergreen is a sought-after speaker, designer, and researcher. She is best known for bringing a research-based approach to helping others better communicate their work through more effective graphs, slides, and reports. She holds a PhD from Western Michigan University in interdisciplinary research, which included a dissertation on the extent of graphic design use in written data reporting. Dr. Evergreen has trained audiences worldwide through keynote presentations and workshops for clients, such as Verizon, Head Start, American Institutes for Research, Brookings Institute, the Ad Council, Boys and Girls Club of America, and the United Nations. She led the first known attempt to revamp the quality of presentations for an entire association: the Potent Presentations Initiative for the American Evaluation Association (AEA). She is the 2015 recipient of the AEA’s Marcia Guttentag Promising New Evaluator Award, which recognizes early notable and substantial accomplishments in the field. Dr. Evergreen is coeditor and coauthor of two issues of New Directions for Evaluation on data visualization. She writes a popular blog on data presentation at StephanieEvergreen.com. Her book, Presenting Data Effectively: Communicating Your Findings for Maximum Impact, was published by Sage in Fall 2013 and was listed as number one in Social Science Research on Amazon in the United States and United Kingdom for several weeks.