Math/CS 484 -- The goal of our Ford/Knight project is to distill and organize the principles of visualizing large data sets. Modern science is often done by small groups of people that come from diverse backgrounds, e.g. a mathematician, a biologist, and a computer scientist. We plan to solicit input in the form of example data sets to work with from each of the natural and social science departments on campus. This work will provide a foundation for a course, or course module, which we hope to offer in the future. Must see instructor for registration.
First Reading and Tips and Techniques Tour
Listed below are the assignments for each chunk, note that everyone should read the startup materials.
- Startup - Everyone
- Web site - Leif
- Making presentations - Mikel
- News graphics - Ivan
- Financial Data - Elena
- Decision making - Emily
- Narrative - Dee
- Aesthetics - Tristan
- Graphic design - Alex
- Scientific and engineering - Mobeen
- Animations - Ryan
As you read your chunks look for bits of guidance, advice, technique, etc. that you feel are useful. Summarize each of these in our Tips and Techniques Google Doc, make sure each entry contains an appropriate citation and follows the pattern/example at the top of the document. This tour is due Sunday 2 September.
First Lab - Measuring the Real World
Measuring the real world, the PDF. This lab is due Sunday 9 September. Turn in a (BW) printout of your writeup and visualization, along with the URL of the on-line (color) version of the visualization if it is available.
First Workshop - Histograms
This assignment is designed to consolidate your knowledge with histograms and give you experience generating one with a modest data set. You must do the work by hand, you can optionally use a software tool to produce it as well. Make sure you document each step of your work. This workshop is due Thursday 13 September.
- Thursday 23 August
- Anscombe's data sets - http://en.wikipedia.org/wiki/Anscombe's_quartet
- Sunday 26 August (retrieve notes from board pictures)
- Relative error, absolute error, systematic error, and related topics
- Standard deviation
- Precision and accuracy
- Thursday 6 September (harvest from Mic)
- Tuesday 11 September (harvest notes from board picture)
- Thursday 14 September
- Answered questions about first lab.