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| + | Demystifying Visual Analytics, ''IEEE Computer Graphics and Applications, March/April 2009'' e-journal @smu library '''Must read!''' | ||
| − | + | Visual Analytics - Mastering the Information Age [http://www.youtube.com/watch?v=5i3xbitEVfs]'''Must view!''' | |
| − | + | Visual analysis for everyone [http://www.tableausoftware.com/whitepapers/visual-analysis-everyone] | |
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|Day 4||60 mins|| | |Day 4||60 mins|| | ||
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Tools for Visualising [http://www.visualisingdata.com/index.php/resources/] | Tools for Visualising [http://www.visualisingdata.com/index.php/resources/] | ||
| − | + | The beauty of data visualization [http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html]'''Must view!''' | |
| + | Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [http://www.abs.gov.au/ausstats/abs@.nsf/mf/1211.0.55.001] | ||
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| − | |Day 5|| | + | |Day 5||3 hours|| |
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| + | Self-learning Tableau | ||
| + | * Getting Started [http://www.tableau.com/learn/tutorials/on-demand/getting-started] | ||
| + | * Tableau Interface [http://www.tableau.com/learn/tutorials/on-demand/tableau-interface] | ||
| + | * Connecting to Data: From Getting Started with Data to Data Blending [http://www.tableau.com/learn/tutorials/on-demand/getting-started-data] | ||
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Latest revision as of 10:08, 14 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
Daily Readings
| Day | Time required | Readings |
| Day 1 | 60 mins |
The best stats you've ever seen [1]Must view! A Tour through the Visualization Zoo [2]Must read! |
| Day 2 | 60 mins |
Why Visual Analytics [3]Must view! Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [4]Must read! Robert Kosara (2012) Visualization: It’s More than Pictures! [5]Must read! |
| Day 3 | 60 mins |
Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library Must read! Visual Analytics - Mastering the Information Age [6]Must view! Visual analysis for everyone [7] |
| Day 4 | 60 mins |
Tools for Visualising [8] The beauty of data visualization [9]Must view! Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [10] |
| Day 5 | 3 hours |
Self-learning Tableau |
References
James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [14]
