• 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.
• 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.
• DATAfiles: 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.
• 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.
• 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.
• 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.
• 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.
• 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.

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 and associate dean of business analytics 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, he 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 many professional journals, including Science, Management Science, Operations Research and the INFORMS Journal on Applied Analytics. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati, and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, Dr. Camm has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of the INFORMS Journal on Applied Analytics (formerly Interfaces). In 2016, Dr. Camm received the George E. Kimball Medal for service to the operations research profession, and in 2017 he was named an INFORMS fellow.

James J. Cochran

James J. Cochran is associate dean for research, professor of applied statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S. and M.B.A. from Wright State University and his Ph.D. from the University of Cincinnati. He has been at The University of Alabama since 2014 and has served as 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 50 papers in the development and application of operations research and statistical methods. He has published in numerous journals, including 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 on Applied Analytics and Statistics and Probability Letters. Dr. Cochran received the 2008 INFORMS Prize for the Teaching of Operations Research Practice, the 2010 Mu Sigma Rho Statistical Education Award and the 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005 and was named a fellow of the American Statistical Association in 2011 and a fellow of INFORMS in 2017. He also received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In addition, he received the INFORMS President's Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has also served as an operations research consultant to numerous companies and not-for-profit organizations.

Michael J. Fry

Michael J. Fry is professor of operations, business analytics and information systems (OBAIS) 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, Dr. Fry earned a B.S. from Texas A&M University and M.S.E. and Ph.D. degrees from the University of Michigan. He has been at the University of Cincinnati since 2002, where he served as department head from 2014 to 2018. Dr. Fry has been named a Lindner Research fellow. He has also been a visiting professor at Cornell University and at the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, Manufacturing & Service Operations Management, Transportation Science, Naval Research Logistics, IIE Transactions, Critical Care Medicine and INFORMS Journal of Applied Analytics. He serves on editorial boards for journals such as Production and Operations Management, INFORMS Journal of Applied Analytics (formerly Interfaces) and Journal of Quantitative Analysis in Sports. His research interests focus on applying analytics to the areas of supply chain management, sports and public-policy operations. He has worked with many different 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 & Botanical Gardens. In 2008, he 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. In 2019, Dr. Fry led the team that was awarded the INFORMS UPS George D. Smith Prize on behalf of the OBAIS Department at the University of Cincinnati.

Jeffrey W. Ohlmann

Jeffrey W. Ohlmann is associate professor of business analytics and a 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 M.S. and Ph.D. degrees from the University of Michigan. Dr. Ohlmann has been at the University of Iowa since 2003. His research on the modeling and solution of decision-making problems has produced more than two dozen research papers published in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science and the European Journal of Operational Research. He has collaborated with organizations such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections and three National Football League franchises. Because of the relevance of his work to industry, Dr. Ohlmann received the George B. Dantzig Dissertation Award, and he was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.