Course pages 2013–14

# Graphs, maths, algorithms, figures and tables

## Videos of the lectures

You can view
the 2012 versions of the lectures:**Good and bad graphs** (24 minutes)**Figures, Tables, Maths, Algorithms** (25 minutes)**Two live examples of creating basic graphs** (15 minutes)**Two live examples of using graphs to explore data** (10 minutes)

## Resources

- Lecture 3 ("Good & Bad Graphs") of Ross Ihaka's course on Information Visualisation is a good introduction to some of things to watch for when graphing.
- Edward Tufte has produced
excellent and beautiful books on visualising information:
*The Visual Display of Quantitative Information*,*Envisioning Information*,*Visual Explanations*, and*Beautiful Evidence*. - Steve Simon has some nice Guidelines for Good Graphics (290kB PDF), which includes references to the academic papers that justify each of his rules (see below).
- Neil Dodgson has produced a case study (104kB PDF) of the figures, tables, and graphs in his 2011 SPIE paper (3MB PDF), written with 2009-10 MPhil student Melinos Averkiou.
- Neil Dodgson has made a simple example of how to improve the readability of a table of results.

## Notes

### Good & Bad Graphs: Concepts

Based on Ross Ihaka's lecture (see above).

**The basics**Choose the correct type of graph for the data. Label the graph. Label the axes.**Data content**Small amounts of data do not require graphs. The human brain can easily grasp one, two or three values.**Data relevance**You cannot produce a good graph from bad data: graphs are only as good as the data they display.**Complexity**Graphs should be no more complex than the data they display. Avoid "chart junk": irrelevant decoration, unnecessary colour, 3D effects. Use the ink to display the data, not junk.**Distortion**Graphs should not give a distorted picture of the values they portray.**Story**Decide what "story" you want the graph to tell. The same data can tell many stories, what is important for communicating your ideas?

### Six Principles for Good Graphics

Based on Steve Simon's notes (see above).

**The Minimum Ink Principle**Avoid gimmicks like pseudo 3-D effects or fancy crosshatching. Use the minimum amount of ink to get your point across.**The Small Table Principle**A small table is better than a large graph. If your graph contains 20 data points or less, consider a table of numbers instead.**The Error of Error Bars Principle**Error bars are confusing and ambiguous. Plot all the data if possible, or use a box plot.**The Size and Shape Principle.**Carefully consider the size and shape of your graph. Rectangular graphs are sometimes better than square graphs. Bigger is not always better.**The Reproduction and Reduction Principle**Colours, shades of gray, and small symbols may get lost when a journal prints your graph, when a student photocopies your graph, or when a colleague prints your graph on a poor printer. Make sure your graphs can withstand reproduction and reduction.**The Fault of Default Principle**Graphing is an iterative process. Do nt rely on the default options provided by your graphics package. Try everything. Re-draw your graphs as often as you rewrite your text.