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 Edward R. Tufte's general theory of graphics display put forth in his book “The Visual Display of Quantitative Information” (VDQI).

Below are some extra resources.

Some websites on charts:

• http://www.visualcomplexity.com/
• Juise Labs Chart Chooser
• Types of Charts: Choose the Best Chart to Convey Your Message
• Nuts and Bolts of Chart & Graph Types
• http://www.typesofgraphs.com/

Articles 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)
• Hannah Groch-Begley & David Shere (2012), A History Of Dishonest Fox Charts (link)

Articles regarding Tufte and his theory:

• Fran Smith's profile of Tufte: Intelligent Designs.
• UCSD Prof. James Hollan's 2013 Information Visualization Seminar on VDQI and Tufte's “Envisioning Information” book. A lot of the links are dead, but especially check out the discussions.
• Prof. Karen Thompson (University of Idaho)'s presentation slides on Data Visualization Theory contrast Tufte and Nigel Holmes.
• Jen Underwood's presentation slides on Data Visualization Best Practices provide a different perspective and lots of links to resources.

Resources on color:

• Visualization 1 from last year.
• 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)