Difference between revisions of "Lesson02"

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<font size =5>'''Show Me the Numbers: Designing Graphs for Data Discovery'''</font>
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<font size = 3>[[Media:ISSS608_Lesson02.pdf|Lesson 2 slides in pdf]]</font> or [http://slides.com/tskam/isss608-lesson02 web slides]
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== Content ==
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Data Foundation
 +
*  Types of data
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*  Structure within and between records
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*  Data preprocessing: ETL (Extract, Transform, and Loading)
 +
 +
Designing Charts to Enlighten
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*  What we mean by an enlighten graph
 +
*  JunkCharts: Understand the limitation of Excel charts
 +
*  Principles of Graphic Design
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*  Semiology of graphics
 +
 +
 +
Human Perception and Information Processing
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*  What Is Perception?
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*  Physiology
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*  Perceptual Processing
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*  Perception in Visualization
 +
*  Metrics
 +
 +
Perceptual and Design Principles for Effective Visual Analytics
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*  System, Color, Gestalt Laws, Pre-attentive processing
 +
*  Representation: The encoding of value and relation
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*  Visual Perception and Quantitative Communication
 +
 +
Visualising and Analysing Univariate Data
 +
*  Data discovery with histogram
 +
*  Data discovery with boxplot
 +
 +
Visualising and Analysing Bivariate Continuous Data
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* Exploring two continuous variables (i.e. scatter plot)
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* Correlation analysis
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* Bivariate data analysis best practices
 +
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Visualising and Analysing One Categorical and One Continuous Data
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* Exploring relationship between one category variable and one continuous variable
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* Performing simple logistic regression
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* Bivariate data visualisation best practices
 +
 +
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== Hands-on Session ==
 +
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*  Visualising and analysing bivariate continuous data using scateerplot
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*  Visualising and analysing bivariate continuous data using mosaic plot
 +
*  Visualising and analysing one continuous and one continuous variables trellis
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== Daily Readings ==
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{| border="1" cellpadding="1"
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|-
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|width="40pt"|Day
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|width="40pt"|Time required
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|width="400pt"|Readings
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|-
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|Day 1||60 mins||
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The Golden Age of Statistical Graphics [http://datavis.ca/papers/golden-STS268.pdf]
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Eight Principles of Data Visualization [http://www.information-management.com/news/Eight-Principles-of-Data-Visualization-10023032-1.html?zkPrintable=1&nopagination=1]
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The Dataviz Design Process: 7 Steps for Beginners [http://annkemery.com/dataviz-design-process/]
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|-
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|Day 2||60 mins||
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Tapping the Power of Visual Perception [http://www.perceptualedge.com/articles/ie/visual_perception.pdf]
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Quantitative Literacy Across the Curriculum [http://www.perceptualedge.com/articles/visual_business_intelligence/quantitative_literacy_across_curriculum.pdf]
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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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|-
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|Day 3||60 mins||Best Practices for Understanding Quantitative Data [http://www.perceptualedge.com/articles/b-eye/quantitative_data.pdf]
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Data Visualization: Rules for Encoding Values in Graph [http://www.perceptualedge.com/articles/b-eye/encoding_values_in_graph.pdf]
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7 Basic Rules for Making Charts and Graphs [http://flowingdata.com/2010/07/22/7-basic-rules-for-making-charts-and-graphs/]
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|-
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|Day 4||60 mins||
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Choosing Colors for Data Visualization [http://www.perceptualedge.com/articles/b-eye/choosing_colors.pdf]
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Line Graphs and Irregular Intervals: An Incompatible Partnership [http://www.perceptualedge.com/articles/visual_business_intelligence/line_graphs_and_irregular_intervals.pdf]
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Self-learning Tableau (30 minutes)
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|-
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|Day 5||60 mins||'''Working with Tableau'''
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Getting Started with Visual Analytics [http://www.tableau.com/learn/tutorials/on-demand/getting-started-visual-analytics]
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Pareto Chart [http://www.tableau.com/learn/tutorials/on-demand/pareto-charts]
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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]
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Histogram [http://www.tableau.com/learn/tutorials/on-demand/histograms]
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|-
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|-
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|}
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== References ==
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Robbins, Naomi B. (2005) Creating More Effective Graphs, John Wiley & Sons, New Jersey, USA.
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Edward R. Tufte (2001) The Visual Display of Quantitative Information (2nd Edition), Graphics press, Connecticut, USA. Chapter 4-9
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Stephen Few (2004) Show Me the Numbers: Designing Tables and Graphs to Englighten, Analytical Press, Oakland, USA.
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Wong, Dona M. (2010) The Wall Street Journal Guide to Information Graphics, W. W. Norton & Company, Inc. New York.
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== Discussion ==
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[[Talk:Lesson02|Discussion Lesson 02]]

Latest revision as of 18:46, 22 August 2016

Vaa.jpg ISSS608 Visual Analytics and Applications

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

 


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.


Discussion

Discussion Lesson 02

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