Data Visualization,
1st Edition

1. Introduction.
2. Selecting a Chart Type.
3. Data Visualization and Design.
4. Purposeful Use of Color.
5. Visualizing Variability.
6. Exploring Data Visually.
7. Explaining Visually to Influence with Data.
8. Data Dashboards.
9. Telling the Truth with Data Visualization.

• Jeffrey D. Camm

  Jeffrey D. Camm is the Inmar Presidential Chair of Analytics and Senior Associate Dean of Business Analytics programs in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, Dr. Camm served on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010, Dr. Camm served as editor-in-chief of INFORMS Journal of Applied Analytics (formerly Interfaces). In 2017, he was named an INFORMS fellow.

• James J. Cochran

  James J. Cochran is Professor of Applied Statistics, the Rogers-Spivey Faculty Fellow and Associate Dean for Faculty and Research at the University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S., and M.B.A. degrees from Wright State University and his Ph.D. from the University of Cincinnati. Dr. Cochran has served at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 45 papers in the development and application of operations research and statistical methods. He has published his research in Management Science, The American Statistician, Communications in Statistics-Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, INFORMS Journal of Applied Analytics and Statistics and Probability Letters. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. Dr. Cochran was elected to the International Statistics Institute in 2005 and named a fellow of the American Statistical Association in 2011. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and was named a fellow of INFORMS. In 2018 he received the INFORMS President’s Award. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.

• Michael J. Fry

  Michael J. Fry is Professor of Operations, Business Analytics and Information Systems and Academic Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University and his M.S.E. and Ph.D. from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department head. Dr. Fry has been named a Lindner Research Fellow. He has also been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IISE Transactions, Critical Care Medicine and INFORMS Journal of Applied Analytics (formerly Interfaces). His research interests are in applying quantitative management methods to the areas of supply chain analytics, sports analytics and public-policy operations. He has worked with many organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo and Botanical Garden. Dr. Fry was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati.

• Jeffrey W. Ohlmann

  Jeffrey W. Ohlmann is Associate Professor of Management Sciences and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska, and his M.S. and Ph.D. from the University of Michigan. He has been at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science, the European Journal of Operational Research and INFORMS Journal of Applied Analytics (formerly Interfaces). He has collaborated with companies such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

• DATA VISUALIZATION Makeover: With the exception of chapter 1, each chapter contains a DATA VISUALIZATION Makeover. Each of these vignettes presents a real visualization that can be improved using the principles discussed in the chapter. We present the original data visualization, and then discuss how it can be improved. The examples are drawn from many different organizations in a variety of areas including government, retail, sports, science, politics, and entertainment.

• Learning Objectives: Each chapter has a list of the learning objectives for that chapter. The list provides details of what the student should be able to do and understand once they have completed the chapter.

• Software: Because of its wide-spread use and ease of availability, we have chosen Microsoft Excel as the software to illustrate the best practices and principles contained herein. Excel has been thoroughly integrated throughout this textbook. Whenever we introduce a new type of chart or table, we provide detailed step-by-step instructions for how to create the chart or table in Excel. For those instructors wishing to use Power BI or Tableau, MindTap will include tip sheets for both that provide step-by-step instructions for recreating the charts from the book using those packages.

• Notes and Comments: At the end of many sections, we provide Notes and Comments to give the student additional insights about the material presented in that section. Additionally, margin notes are used throughout the textbook to provide additional insights and tips related to the specific material being discussed.

• End-of-Chapter Problems: Each chapter contains at least 15 problems to help the student master the material presented in that chapter. The problems are separated into Conceptual and Application problems. Conceptual problems test the student's understanding of concepts presented in the chapter. Application problems are hands-on, and require the student to construct or edit charts or tables.

• DATAfiles and CHARTfiles: All data sets used as examples and in end-of-chapter problems are Excel files designated as DATAfiles and are available for download by the student. The names of the DATAfiles are called out in margin notes throughout the textbook. Similarly, Excel files with completed charts are available for download and are designated as CHARTfiles.

• MindTap, a highly customizable digital course solution, offers an interactive eBook, auto-graded and randomized exercises and problems from the textbook, algorithmic Excel activities, chapter overview and problem walk-through videos, and interactive visualizations to strengthen students' understanding of course concepts.

• Available in MindTap only, 'Tip Sheets' for both Tableau and Power BI are available that cover step-by-step how to recreate the charts and tables covered in the book using these two popular data visualization packages.

Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.

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