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Revision as of 08:56, 9 August 2016
ISSS608 Visual Analytics and Applications
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Demystifying Visual Analytics
Content
Introduction to the course
- Why this course?
- What does it cover?
- Who is involved?
- What assignments?
- Rules to be followed
Motivations of Visual Analytics
- Massive data
- Complex problem
- Visual Representation
- New visual paradigm
- Hidden insight
The Visual Analytics Framework
- The Science of Analytical Reasoning
- Sense-Making Methods
- Components of visual analytics
- History of visual analytics
- The visual analytics process
- Application challenges
- Technical challenges
A Gallery of Visual Analytics applications
Visualising and Analysing Univariate Data
- Data discovery with bar chart
- Data discovery with dotplot
Visualising and Analysing Bivariate Categorical Data
- Exploring two categorical variables
- Working with mosaic plot and trellis
- Bivariate categorical data analysis best practices
Hands-on Session
Self-learning Tableau
- Getting Started [1]
- Tableau Interface [2]
- Connecting to Data: From Getting Started with Data to Data Blending
Daily Readings
| Day | Time required | Readings |
| Day 1 | 60 mins |
The best stats you've ever seen [3]Must view! A Tour through the Visualization Zoo [4]Must read! |
| Day 2 | 60 mins |
Why Visual Analytics [5]Must view! Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [6]Must read! Robert Kosara (2012) Visualization: It’s More than Pictures! [7]Must read! |
| Day 3 | 3hrs |
Lesson 01
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| Day 4 | 60 mins |
Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library Must read! The beauty of data visualization [8]Must view! Tools for Visualising [9] Visual analysis for everyone [10] |
| Day 5 | 60 mins |
Visual Analytics - Mastering the Information Age [11]Must view! Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [12] |
References
James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [13]
