Effective Data Visualization: The Right Chart for the Right Data

This comprehensive how-to guide functions as a set of blueprints—supported by research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. 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 making the chosen graph in Excel.  Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Table of Contents:
1. Our Backbone: Why We Visualize Why We Visualize When Visualization Is Harmful Which Chart Type Is Best? How to Use This Book Exercises Resources References 2. When a Single Number Is Important: Showing Mean, Frequency, and Measures of Variability What Stories Can Be Told With a Single Number? How Can I Visualize a Single Number? How Can I Show Measures of Variability? Exercises Resources References 3. How Two or More Numbers are Alike or Different: Visualizing Comparisons What Stories Can Be Told About How Two or More Numbers Are Alike or Different? How Can I Visualize How Two or More Numbers Are Alike or Different? Exercises Resources References 4. How We Are Better or Worse Than a Benchmark: Displaying Relative Performance What Stories Can Be Told About How We Are Better or Worse Than a Benchmark? How Can I Visualize How We Are Better or Worse Than a Benchmark? Exercises Resources References 5. What the Survey Says: Showing Likert, Ranking, Check-All-That-Apply, and More What Stories Can Be Told About What the Survey Says? How Can I Visualize What the Survey Says? Ranking Branching Visualizing Not Applicable or Missing Data Exercises Resources References 6. When There Are Parts of a Whole: Visualizing Beyond the Pie Chart What Stories Can Be Told When There Are Parts of a Whole? How Can I Visualize the Parts of a Whole? Exercises Resources References 7. How This Thing Changes When That Thing Does: Communicating Correlation and Regression What Stories Can Be Told About How This Thing Changes When That Thing Does? How Can I Visualize How This Thing Changes When That Thing Does? Exercises Resources References 8. When the Words Have the Meaning: Visualizing Qualitative Data What Stories Can Be Told When the Words Have the Meaning? How Can I Visualize When the Words Have the Meaning? Exercises Resources References 9. How Things Changed Over Time: Depicting Trends What Stories Can Be Told About How Things Changed Over Time? How Can I Visualize How Things Changed Over Time? Exercises Resources References 10. It's About More Than the Buttons Dot Plots Generate Healthcare Pioneers Clearly Labeled Line Graphs Streamline Decisions at a Fortune 500 Diverging Stacked Bars Make for Community Leaders in the Midwest Icons Support Informed Policymaking Exercises Resources Reference

About the Author :
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.

Review :
This text brings data visualization in to the twenty-first century. It is a definitive guide for students and practitioners in presenting data with clarity and lucidity. Very approachable writing style, clear examples and instructions make this a “must-have” for anyone who has to present data. I love this book. It opened me up to so many possibilities that I didn’t know existed in Excel. The author really helps you build these skills though thoughtful exercises. She uses her real-world experience to open the “black-box” behind graphing techniques. I can’t wait to use these skills for my next batch of research projects. The competition at the professional conferences will be amazed by our ninja skills. This run-to-read and easy-to-use book can boost your visual presentation by making it right to the point! Effective Data Visualization sets a new standard for the practical presentation data using Excel. It provides impressive graphics and hands on details on when and  how to present them to various audiences. Any instructor who works with students seeking an advanced professional degree should consider adopting this text. This book is an excellent guide for creating innovative and intentional graphics that can frequently speak for themselves. Stephanie not only shows you how to create visually appealing charts and graphics, but she also explains why it matters.