Abstract: Visualization is an effective method for communicating quantitative information, and in particular can aid in the demonstration of relationships and patterns within data. Data visualization has become more prevalent as a method of communicating information in the last several decades, with charts regularly showing up on social media platforms, in news media, and in everyday applications such as fitness trackers, weather forecasting, and financial and utility bills. As such, the U.S. adult population increasingly uses visual displays of quantitative information to inform decision-making about their own lives. There is a rich literature in studying graphical perception and how humans perceive data graphics; however, much prior work focuses on the perception of shapes and forms as stand-alone elements rather than holistic interpretation or understanding of the content in a designed data visualization. Further, many user studies have been completed with small or biased samples, often including overrepresentations of adults with high educational attainment. In this presentation, I will discuss our ongoing work to study understanding of data visualizations among U.S. adults using a nationally-representative sample of survey respondents, including our approach to experimental design, findings on overall understanding of data graphics among U.S. adults, and differences across key demographics.

About the Speaker: Dr. Kiegan Rice is a senior statistician in the Statistics & Data Science department at NORC. In this role, she serves as an expert in data visualization, statistical modeling, and computational reproducibility, and leads the development of web-based interactive data visualization tools. She also has expertise in automated data reporting and reproducible data analysis pipelines. Kiegan has built a variety of public-facing interactive dashboards and data visualizations, including the NEAS Pathways Tool and MCBS Interactives site. In addition, she has led the development and maintenance of interactive applications and automated data reporting processes for several clients including the Bill and Melinda Gates Foundation, College Board, and the National Center for Science and Engineering Statistics. Kiegan is also an expert on reproducibility in data science workflows and quantitative research. She has presented on these topics at venues such as rstudio::conf, Government Advances in Statistical Programming (GASP), and the Symposium on Data Science and Statistics (SDSS).