Difference between revisions of "Lesson02"
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| + | <font size =5>'''Designing Graphs to Enlighten: Principles, Methods and Best Practices'''</font> | ||
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| + | <font size = 3>[[media:Lesson02.pdf|Lesson 2 Slides]]</font> or [http://slides.com/tskam/is428-lesson02 web version] | ||
| + | |||
| + | == Content == | ||
| + | |||
| + | Data Foundation | ||
| + | * Types of data | ||
| + | * Structure within and between records | ||
| + | * Data preprocessing: ETL (Extract, Transform, and Loading) | ||
| + | |||
| + | Human Perception and Information Processing | ||
| + | * What Is Perception? | ||
| + | * Physiology | ||
| + | * Perceptual Processing | ||
| + | * Perception in Visualization | ||
| + | * Metrics | ||
| + | |||
| + | Perceptual and Design Principles for Effective Visual Analytics | ||
| + | * System, Color, Gestalt Laws, Pre-attentive processing | ||
| + | * Representation: The encoding of value and relation | ||
| + | * Visual Perception and Quantitative Communication | ||
| + | |||
| + | Designing Charts to Enlighten | ||
| + | * What we mean by an enlighten graph | ||
| + | * JunkCharts: Understand the limitation of Excel charts | ||
| + | * Principles of Graphic Design | ||
| + | * Semiology of graphics | ||
| + | |||
| + | Useful Charts for Data Discovery | ||
| + | * Data discovery with bar chart | ||
| + | * Data discovery with histogram | ||
| + | * Data discovery with boxplot | ||
| + | * Data discovery with dotplot | ||
| + | |||
| + | == Hands-on Session == | ||
| + | |||
| + | * Visualising and analysing bivariate data | ||
| + | * Interactive visual analytics with Graph Builder | ||
| + | |||
| + | |||
| + | == Daily Readings == | ||
| + | |||
| + | {| border="1" cellpadding="1" | ||
| + | |- | ||
| + | |width="40pt"|Day | ||
| + | |width="40pt"|Time required | ||
| + | |width="400pt"|Readings | ||
| + | |- | ||
| + | |||
| + | |Day 1||60 mins|| | ||
| + | Eight Principles of Data Visualization [http://www.information-management.com/news/Eight-Principles-of-Data-Visualization-10023032-1.html?zkPrintable=1&nopagination=1] | ||
| + | |||
| + | The Dataviz Design Process: 7 Steps for Beginners [http://annkemery.com/dataviz-design-process/] | ||
| + | |||
| + | |- | ||
| + | |||
| + | |Day 2||60 mins|| | ||
| + | Tapping the Power of Visual Perception [http://www.perceptualedge.com/articles/ie/visual_perception.pdf] | ||
| + | |||
| + | Quantitative Literacy Across the Curriculum [http://www.perceptualedge.com/articles/visual_business_intelligence/quantitative_literacy_across_curriculum.pdf] | ||
| + | |||
| + | |- | ||
| + | |||
| + | |Day 3||60 mins||Best Practices for Understanding Quantitative Data [http://www.perceptualedge.com/articles/b-eye/quantitative_data.pdf] | ||
| + | |||
| + | Data Visualization: Rules for Encoding Values in Graph [http://www.perceptualedge.com/articles/b-eye/encoding_values_in_graph.pdf] | ||
| + | |||
| + | Sometimes We Must Raise Our Voices [http://www.perceptualedge.com/articles/visual_business_intelligence/sometimes_we_must_raise_our_voices.pdf] | ||
| + | |- | ||
| + | |||
| + | |Day 4||60 mins|| | ||
| + | Choosing Colors for Data Visualization [http://www.perceptualedge.com/articles/b-eye/choosing_colors.pdf] | ||
| + | |||
| + | Line Graphs and Irregular Intervals: An Incompatible Partnership [http://www.perceptualedge.com/articles/visual_business_intelligence/line_graphs_and_irregular_intervals.pdf] | ||
| + | |||
| + | 7 Basic Rules for Making Charts and Graphs [http://flowingdata.com/2010/07/22/7-basic-rules-for-making-charts-and-graphs/] | ||
| + | |||
| + | |- | ||
| + | |||
| + | |Day 5||3 hours||Hands-on exercise: Exploring Tableau | ||
| + | |||
| + | Getting Started with Visual Analytics [http://www.tableau.com/learn/tutorials/on-demand/getting-started-visual-analytics] | ||
| + | |||
| + | Pareto Chart [http://www.tableau.com/learn/tutorials/on-demand/pareto-charts] | ||
| + | |||
| + | Do More with Bar Charts in Tableau 10 [http://www.tableau.com/about/blog/2016/6/mark-sizing-tableau-10-56014] | ||
| + | |||
| + | Boxplot [http://www.tableau.com/learn/tutorials/on-demand/box-plots] | ||
| + | |||
| + | Histogram [http://www.tableau.com/learn/tutorials/on-demand/histograms] | ||
| + | |||
| + | |- | ||
| + | |- | ||
| + | |} | ||
| + | |||
| + | == References == | ||
| + | |||
| + | Robbins, Naomi B. (2005) Creating More Effective Graphs, John Wiley & Sons, New Jersey, USA. | ||
| + | |||
| + | Edward R. Tufte (2001) The Visual Display of Quantitative Information (2nd Edition), Graphics press, Connecticut, USA. Chapter 4-9 | ||
| + | |||
| + | Stephen Few (2004) Show Me the Numbers: Designing Tables and Graphs to Englighten, Analytical Press, Oakland, USA. | ||
| + | |||
| + | Wong, Dona M. (2010) The Wall Street Journal Guide to Information Graphics, W. W. Norton & Company, Inc. New York. | ||
| + | |||
| + | |||
| + | |||
| + | == Discussion == | ||
| + | |||
| + | [[Talk:Lesson02|Discussion Lesson 02]] | ||
Latest revision as of 11:58, 22 August 2016
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Designing Graphs to Enlighten: Principles, Methods and Best Practices
Lesson 2 Slides or web version
Content
Data Foundation
- Types of data
- Structure within and between records
- Data preprocessing: ETL (Extract, Transform, and Loading)
Human Perception and Information Processing
- What Is Perception?
- Physiology
- Perceptual Processing
- Perception in Visualization
- Metrics
Perceptual and Design Principles for Effective Visual Analytics
- System, Color, Gestalt Laws, Pre-attentive processing
- Representation: The encoding of value and relation
- Visual Perception and Quantitative Communication
Designing Charts to Enlighten
- What we mean by an enlighten graph
- JunkCharts: Understand the limitation of Excel charts
- Principles of Graphic Design
- Semiology of graphics
Useful Charts for Data Discovery
- Data discovery with bar chart
- Data discovery with histogram
- Data discovery with boxplot
- Data discovery with dotplot
Hands-on Session
- Visualising and analysing bivariate data
- Interactive visual analytics with Graph Builder
Daily Readings
| Day | Time required | Readings |
| Day 1 | 60 mins |
Eight Principles of Data Visualization [1] The Dataviz Design Process: 7 Steps for Beginners [2] |
| Day 2 | 60 mins |
Tapping the Power of Visual Perception [3] Quantitative Literacy Across the Curriculum [4] |
| Day 3 | 60 mins | Best Practices for Understanding Quantitative Data [5]
Data Visualization: Rules for Encoding Values in Graph [6] Sometimes We Must Raise Our Voices [7] |
| Day 4 | 60 mins |
Choosing Colors for Data Visualization [8] Line Graphs and Irregular Intervals: An Incompatible Partnership [9] 7 Basic Rules for Making Charts and Graphs [10] |
| Day 5 | 3 hours | Hands-on exercise: Exploring Tableau
Getting Started with Visual Analytics [11] Pareto Chart [12] Do More with Bar Charts in Tableau 10 [13] Boxplot [14] Histogram [15] |
References
Robbins, Naomi B. (2005) Creating More Effective Graphs, John Wiley & Sons, New Jersey, USA.
Edward R. Tufte (2001) The Visual Display of Quantitative Information (2nd Edition), Graphics press, Connecticut, USA. Chapter 4-9
Stephen Few (2004) Show Me the Numbers: Designing Tables and Graphs to Englighten, Analytical Press, Oakland, USA.
Wong, Dona M. (2010) The Wall Street Journal Guide to Information Graphics, W. W. Norton & Company, Inc. New York.