December 4-8, 2017 at Atlantic City, New Jersey
The 73rd Deming Conference on Applied Statistics
Sponsored by Metropolitan Section, ASQ and Biopharmaceutical Section, ASA

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12/5/2016 (Monday) 8:30 AM - 11:45 AM

Session A: Data display for statistical analysis

Prof. Richard Heiberger, Temple University

Moderator: Walter Young
Complex data analyses may require complex graphs to place the full information of the analysis into a form that the intended client will be able to read. Data analysts are responsible for the display of data with graphs and tables that summarize and represent the data and the analysis. Graphs are often the output of data analysis that provides the best means of communication between the data analyst and the client. Gaining an understanding of a data set is always more easily accomplished by looking at appropriately drawn graphs than by examining tabular summaries. We will look at many examples of graphs, from simple to complex. We need to begin with simple graphs to learn the vocabulary of graphs. We then proceed to more complex graphs and see how they are constructed by using the same graphic vocabulary. We discuss the principles of good graphs and show why they are important for communication between the data analyst and the client. Topics include: the design of multi-panel graphics; graphing Likert Scale Data to build on the importance of rating scales; the design of graphics that will work for readers with color-deficient vision; and interactive graphs. Most of the examples will be from the medical/pharmaceutical areas or from social sciences. The concepts are much more broadly applicable.

Richard M. Heiberger (PhD in Statistics from Harvard) is Professor Emeritus of Statistics in the Fox School at Temple University. His primary research area is statistical computing, with emphasis in statistical graphics, software design, linear models, and design of experiments. He was Graduate Chair for the Department of Statistics from 1983 to 1987 and Acting Associate Vice Provost for the University in 1989 to 1990. Professor Heiberger has served as statistics consultant at Bell Labs and at GlaxoSmithKline. He has taught short courses at the annual American Statistical Association Joint Statistical Meetings, at the Deming Conference on Applied Statistics, and in industry. His undergraduate degree in Mathematics is from Oberlin College. He is an elected Fellow of the American Statistical Association and was the 2011 Chair of the ASA Section on Statistical Computing.

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