Difference between revisions of "Lesson02"
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<font size =5>'''Show Me the Numbers: Designing Graphs for Data Discovery'''</font> | <font size =5>'''Show Me the Numbers: Designing Graphs for Data Discovery'''</font> | ||
| − | <font size = 3>[[Media:ISSS608_Lesson02.pdf|Lesson 2 slides]]</font> | + | <font size = 3>[[Media:ISSS608_Lesson02.pdf|Lesson 2 slides in pdf]]</font> or [http://slides.com/tskam/isss608-lesson02 web slides] |
== Content == | == Content == | ||
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{| border="1" cellpadding="1" | {| border="1" cellpadding="1" | ||
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| − | |width=" | + | |width="40pt"|Day |
| − | |width=" | + | |width="40pt"|Time required |
| − | |width=" | + | |width="400pt"|Readings |
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| − | + | |Day 1||60 mins|| | |
| + | The Golden Age of Statistical Graphics [http://datavis.ca/papers/golden-STS268.pdf] | ||
| − | + | 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/] | ||
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| + | |||
| + | |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] | ||
| + | |||
| + | Sometimes We Must Raise Our Voices [http://www.perceptualedge.com/articles/visual_business_intelligence/sometimes_we_must_raise_our_voices.pdf] | ||
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| − | |||
| − | |||
| − | + | |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] | |
| + | 7 Basic Rules for Making Charts and Graphs [http://flowingdata.com/2010/07/22/7-basic-rules-for-making-charts-and-graphs/] | ||
|- | |- | ||
| + | |||
| + | |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] | ||
| + | |||
| + | Self-learning Tableau (30 minutes) | ||
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| − | + | |Day 5||60 mins||'''Working with 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] | |
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| − | + | Boxplot [http://www.tableau.com/learn/tutorials/on-demand/box-plots] | |
| − | + | Histogram [http://www.tableau.com/learn/tutorials/on-demand/histograms] | |
| − | |||
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Latest revision as of 18:46, 22 August 2016
ISSS608 Visual Analytics and Applications
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Show Me the Numbers: Designing Graphs for Data Discovery
Lesson 2 slides in pdf or web slides
Content
Data Foundation
- Types of data
- Structure within and between records
- Data preprocessing: ETL (Extract, Transform, and Loading)
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
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
Visualising and Analysing Univariate Data
- Data discovery with histogram
- Data discovery with boxplot
Visualising and Analysing Bivariate Continuous Data
- Exploring two continuous variables (i.e. scatter plot)
- Correlation analysis
- Bivariate data analysis best practices
Visualising and Analysing One Categorical and One Continuous Data
- Exploring relationship between one category variable and one continuous variable
- Performing simple logistic regression
- Bivariate data visualisation best practices
Hands-on Session
- Visualising and analysing bivariate continuous data using scateerplot
- Visualising and analysing bivariate continuous data using mosaic plot
- Visualising and analysing one continuous and one continuous variables trellis
Daily Readings
| Day | Time required | Readings |
| Day 1 | 60 mins |
The Golden Age of Statistical Graphics [1] Eight Principles of Data Visualization [2] The Dataviz Design Process: 7 Steps for Beginners [3] |
| Day 2 | 60 mins |
Tapping the Power of Visual Perception [4] Quantitative Literacy Across the Curriculum [5] Sometimes We Must Raise Our Voices [6] |
| Day 3 | 60 mins | Best Practices for Understanding Quantitative Data [7]
Data Visualization: Rules for Encoding Values in Graph [8] 7 Basic Rules for Making Charts and Graphs [9] |
| Day 4 | 60 mins |
Choosing Colors for Data Visualization [10] Line Graphs and Irregular Intervals: An Incompatible Partnership [11] Self-learning Tableau (30 minutes) |
| Day 5 | 60 mins | Working with Tableau
Getting Started with Visual Analytics [12] Pareto Chart [13] Do More with Bar Charts in Tableau 10 [14] Boxplot [15] Histogram [16] |
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.
