Communicating your findings to an audience is a critical part of science. This lecture is about this communication process and in particular about how to present your data with tables and graphs. We discuss the basic anatomy and different types of charts and tables, when to use which, some common mistakes and how to use color.

You can download the presentation slides here.

The lecture refers to RM chapter 16, as well as the following articles (grey = extra).

On color:

• Bernice E. Rogowitz & Lloyd A. Treinish (1996), Why Should Engineers and Scientists Be Worried About Color?, IBM Thomas J. Watson Research Center (link)
• Kenneth Moreland (2009), Diverging Color Maps for Scientific Visualization, Proceedings of the 5th International Symposium on Visual Computing (link)
• Lawrence D. Bergman, Bernice E. Rogowitz & Lloyd A. Treinish (1995), A Rule-based Tool for Assisting Colormap Selection, IBM Thomas J. Watson Research Center (link)
• http://en.wikipedia.org/wiki/Complementary_colors
• http://en.wikipedia.org/wiki/Opponent_process
• Maureen Stone (2006), Choosing Colors for Data Visualization (pdf)
• David Borland and Russell M. Taylor II (2007), Rainbow Color Map (Still) Considered Harmful, IEEE Computer Graphics and Applications (pdf)
• cresspahl (2012), The 'jet' colormap must die! Or: how to improve your map plots and create your own nice colormaps. (link)
• Robert Kosara (2013), How The Rainbow Color Map Misleads (link)

On misleading graphs:

• Ravi Parikh (2014), How to Lie With Data Visualization, Gizmodo (link)
• Naomi Robbins (2012), Bill Clinton's Speech in Misleading Graphs, Forbes (link)
• Ian C. Campbell (2012), Misleading with pictures: The pitfalls of data visualization (link)