Statistics 120 - Information Visualisation


This course provides an introduction to visualisation techniques in statistics. Using an understanding of graphical perception, we will examine graphical displays traditionally used in statistics as well as some new ones. We will also look a some computer intensive techniques, including animation, as a means of gaining insight into data in higher dimensions. Topics will consist of a selection taken from the following list.

Why visualise?
Computing for graphics
Human vision and perception
Displays for counts and proportions
Displays for numeric data
Time series displays
Multivariate data
Graphical examination of relationships
Visualisation as an aid to theory
Dynamic graphics

Examples will be drawn from across the physical and social sciences.


The formal prerequisite for the course is a good pass in bursary mathematics or one of the other first-year statistics courses. A reasonable understanding of basic mathematics (geometry and trigonometry) is expected and we will use a tiny amount of calculus (differentiating x2), but will explain this in class. The ability to write clearly is also important.


The lectures for the class are at Monday, Wednesday and Friday 11-12 in Eng3403. The course has a computer laboratory scheduled in the Statistics Department's computer tutorial room (303.175) on Fridays from noon to 2pm.


The final grade for the course will be made up of 15% from assignments, 20% from a mid-semester test, and 65% from the final exam. A minimum of 45% must be obtained in the final exam. The assignments will require a mix of written exposition and graphical presentation. The final exam and test will consist of a number of essay questions. The test for the course is scheduled for Wednesday August 27, 11am - noon.


An important focus of the course is on developing practical computing skills and the class will involve a lot of computing. This computing can be either be done in the Statistics Department's computing laboratory or on your own PC at home at home (Windows, Macintosh or Linux).

Ross Ihaka
Room 275
Statistics Department