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Data visualization is an important tool for researchers, assisting in both analysis and communication of results. The use of appropriate visualization techniques can greatly increase the ability to gain insight from and ease the communication of data.

Creation of effective visual representations relies highly on the use of what are known as visual variables. Visual variables include colour, brightness, position, orientation, shade, and texture. Appropriate use of these properties is a key component of mapping raw data to a visual representation. Through effective use of visual variables a great number of properties can be embedded in a single visualization.

This tutorial consists of three parts: a half-hour lecture describing the effective use of visual variables and different types of visualization; a group exercise in applying visual variables through sketching an example dataset; and through the last 30-40 minutes participants are encouraged to experiment with visual variables on their own data.

Wednesday, April 5, 2017
1:00pm - 2:30pm
HSL 1460A
Health Sciences
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