Lecture topics, reading materials, and resources
08/22 - Week 1: Plotting technologies
Learning objectives:
- Understand the syllabus
- Use Google Sheets (or Microsoft Excel) for data cleaning and analysis
- Use Matplotlib/Seaborn
- Create effective concept maps
- Identify various types of plots
Classroom agenda:
- Introductions
- Review of the syllabus, followed by QnA
- Introduction to Google Sheets - features to demo
a. (1.25 hr) Google sheets beginner tutorial - part 1
b. (1.5 hr) Google sheets beginner tutorial - part 2
(hint: watch in 1.5x to skim through easy topics)
- Introduction to Matplotlib - a tiny example
- Attendance
- Various types of plots
- How this course started - workshop on data visualizations
- Drawing effective concept maps - pdf tutorial / video
- UMSL Health Services - slide
- Your feedback is important!
- Graded quiz (for testing)
Assignments:
- Draw plots using Google Sheets
- Purchase books
- Find one ineffective plot and one highly effective plot (print and bring in the next class)
- Purchase a display board (examples: 1, 2, 3)
Topics for quiz (next week):
- Types of plots
- * Google Sheets
- Concept map tutorial
- Syllabus
Here are sample quiz questions.
08/29 - Week 2: Graphical excellence and qualities of great visualizations
Learning objectives:
- Reflect on the foundations of graphical excellence
- Reflect on the five qualities of great visualizations
- Recognize the fundamental principles of analytical design (in the context of data graphics)
- Deconstruct, analyze, and judge if a plot is effective
Classroom agenda:
- Quiz
- William Playfair (1759 - 1823) - video (1 min)
He developed (or improved upon) the fundamental graphical designs, seeking to replace conventional tables of numbers with systematic visual representations.
- What is graphical excellence? - notes
- Anscombe’s quartet - notes - video (3 min)
Anscombe (1918-2011) showed how the graphs of four sets of 11 data points with almost the same set of descriptive statistics look completely different. This demonstrates why we should visualize data.
- Three excellent space-time-story graphics:
- Classroom activity: Discuss/understand the “Minards chart” and answer the questions
- Terms: visualization, data visualization, data graphics, infographics, etc. - notes
- Increasing your “shoreline of wonder” - notes
- Five qualities of great (persuasive) visualizations - notes
- Classroom activity: Compare “What an excellent graphic should do” by E. Tufte with “Five qualities” by A. Cairo.
- Classroom activity (previous assignment): Let your peers pick ineffective (bad) plots.
Reading assignments:
- TVDQI’s Chapter 1 - Graphical Excellence
- The Beautiful Evidence’s “The Fundamental Principles of Analytical Design”
- PDF at the Canvas discussion board
- TTA’s Introduction - The island of knowledge and shoreline of wonder
- TTA’s Chapter 1 - What we talk about when we talk about visualization
- TTA’s Chapter 2 - The five qualities of great visualizations
Additional reading assignments for graduate students: (only for concept map assignment not for quiz)
- VAD’s Chapter 1 - What’s Vis, and Why do it? - lecture
Assignments:
- Classroom activities (proof of participation)
- Concept map homeworks
- Several homeworks related to the contents of the book chapters
Topics for quiz (next week):
- All book chapters in the reading assignment
- Classroom discussions and contents in the classroom agenda
09/05 - Week 3: Labor day holiday
09/12 - Week 4: Truthfulness and integrity
Learning objectives:
- Understand several bugs (biases) that we have in our mind
- Learn dozens of cognitive/human biases
- Understand how to hypothesize and do experiments
Classroom agenda:
- Quiz
- Office hours updated to Monday
- The truth continuum - slides
- A visualization is a model
- Our mind is a clumsy modeler
- Patternicity bug, storytelling bug, and confirmation bug
- Truth is neither absolute nor relative
- Activity: Find the names for the human bias descriptions - bias list and bias descriptions
- Conjectures & uncertainity - slides
- Activity: Your personal experience that exemplefies a congnitive bias
- Graphical integrity - notes
Reading assignments:
- TTA’s Chapter 3 - The truth continuum
- TTA’s Chapter 4 - Of Conjectures and Uncertainty
- TVDQI’s Chapter 2 - Graphical Integrity
- 120 human (cognitive) biases
Assignments:
- Classroom activities (proof of participation)
- Concept map homeworks
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- Find an untruthful plot/chart in the internet, investigate, and draw a truthful version of it.
–>
Topics for quiz (next week):
- All book chapters in the reading assignment
- Slide contents
- You should be able to match the bias descriptions or example scenarios with the bias names.
09/19 - Week 5: Principles and visual perception
Learning objectives:
- Learn the foundations of visual perception and attributes
- Learn several examples that demonstrate how to choose the right graphic form and organize your graphic display
- Gestalt principles of visual perception
Classroom agenda:
- Quiz
- Basic principles of visualization - slides
- Visual perception and graphical communication - slides
- Applying visual attributes to design
- Gestalt principles of visual perception
- Discussion of assignment
- Visualizations should be naked - notes
- Chartjunks: Vibrations, grids, and ducks - notes
Reading assignments:
- TTA’s Chapter 5 - Basic principles of visualization
- SMTN’s Chapter 5 - Visual perception and graphical communication
- TVDQI’s Chapter 4 - Data ink and graphical redesign
- TVDQI’s Chapter 5 - Chart junk: Vibrations, grids, and ducks
- Pages 107, 110, 111 - 114, 117, 118
- TVDQI’s Chapter 6 - Data-ink maximization and graphical design
- Pages 124 - 137 (entire chapter)
- List and examples of graphic forms
Assignments:
- Classroom activities (proof of participation)
- Concept map homeworks
- One practical problem on choosing the right graphic form
- Two additional practical problems on choosing the right graphic form
- Work in a group of maximum two students
- Print and bring to the next class
- Find one example for all the graphic forms (from the internet)
Additional reading assignments for graduate students: (only for concept map assignment not for quiz)
- VAD’s Chapter 6 - Rules of Thumb - lecture
Topics for quiz (next week):
- Slide materials presented in class
- Book chapter readings
- Match the graphic forms (plot types) with plot names
09/26 - Week 6: Exploring data with simple charts
Learning objectives:
- Deconstruct and create data graphics involving mean, median, and mode appropriately
- Learn to explore data using histograms and strip plots
- Learn to calculate weighted mean
- Deconstruct and create data graphics involving logarithmic scales
Classroom agenda:
- Quiz
- One-minute paper
- Read assignment questions
- Exploring data using simple charts - slides
- Logarithmic scale - slides
- Discuss assignment questions
- Sample mid-term questions
- Submit your one-minute paper
Reading assignments:
- TTA’s Chapter 6 - Exploring data with simple charts
- SMTN’s Chapter 2 - Simple statistics to get you started
Assignments:
- A few excercises involving mean/median/mode
- Several plotting tasks
- NO Concept map assignment
Additional reading assignments for graduate students: (only for concept map assignment not for quiz)
Topics for quiz (next week):
10/03 - Week 7: Comprehensive mid-term (2 hours long)
Topics
- All “plots/charts/data graphics” discussed in the class, assigned in assignment, and in book chapter readings
- Minard’s chart and the “fundamental principles of analytical design”
- Five qualities of great (persuasive) visualizations
- Calculating lie factor
- Principles of graphical integrity
- Gestalt principles of visual perception
- Data-ink ratio
- Removing chartjunks
- Designing plots with logarithmic scale
- The truth continuum
- What is simplicity?
- The scientific stance
- The scale of elementary perceptual tasks
- When to plot in multiple charts (Fig. 5.14, pg. 138)
- Weighted mean (Fig. 6.3, pg. 157)
10/10 - Week 8: Visualizing distributions
Learning objectives:
- Learn to use measures of spread including the standard deviation, appropriately
- Learn to compare distributions with and without standardization
- Learn the limitations of box plots
- Learn how standardized scores can mislead us and funnel plots can help debug
- Learn, with an example, that estimates based on small populations tend to show more variation
Classroom agenda:
Reading assignments:
- TTA’s Chapter 7 - Visualizing distributions
Assignments:
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents from the slides and classroom activities
10/17 - Week 9: Exploring and explaining trends
Learning objectives:
- Decompose time series data into trend, seasonality, and noise
- Elucidate patterns hidden in time series data
- Learn to design effective small multiples
- Learn several techniques for communicating change
- Learn to have fun with ‘Google Finance’ in Google Sheets
- Learn about sparklines
Classroom agenda:
Reading assignments:
- TTA’s Chapter 8 - Revealing Change
- BE’s Chapter 2 - Sparklines: Intense, Simple, Word-Sized Graphics
Assignments:
- Several plotting tasks
- Several analytical questions related to book chapters
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents from the slides and classroom activities, including the chapter on sparklines
- All videos posted in the agenda
10/24 - Seeing relationships
Learning objectives:
- The process of moving from variable independence to association to correlation to causation
- Association vs. correlation
- Usefulness and limitations of calculating correlation
- Designing effective parallel coordinates charts
Classroom agenda:
Reading assignments:
Assignments:
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents on the slide and classroom discussions
- When randomized controlled experiments are not possible, is it still possible to make a case for a causal connection?
- Calculating the coefficient of determination
- Important features when designing parallel coordinates
- Limitations of Pearson’s correlation and Spearman’s rank correlation
- Association vs correlation
10/31 - Table design and Component-level graph design (i.e., the details)
Learning objectives:
- When to use a table instead of a data graphic
- Techniques for designing (and formatting) effective tables
- Techniques to improve a data graphic at the component-level
Classroom agenda:
- Quiz
- Attendance
- Component-level graphic design
- Table design
- Submit your one-minute paper
Reading assignments:
- SMTN’s Chapter 3 - Differing roles of tables & graphs
- SMTN’s Chapter 8 - Table Design
- SMTN’s Chapter 10 - Component-level graph design
Assignments:
- Several questions on designing/redesigning tables and data graphics
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents on the slides, book chapters, and classroom discussions
11/07 - Color and Accessible data visualization
Learning objectives:
- Rules to use color effectively and appropriately
- Ideas to design accessible data graphics
Classroom agenda:
Reading assignments:
Assignments:
- Several tasks on designing/redesigning data graphics
- Several tasks related to color and accessibility
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents on the slides and classroom discussions
11/14 - Evaluating data visualization & Network visualization
Learning objectives:
- A comprehensive toolbox to evaluate a data visualization
- The power of network visualization
Classroom agenda:
- Quiz
- Attendance
- [Demo] Evaluating data visualization
- Google form “Evaluating a data visualization”
- Article on The Happiest States of America
- Summary: The article “The Happiest States of America” summarizes the survey results and informs that Utah is the happiest state in the US. The Gallup-Healthways well-being index (the metric to access happiness) includes factors like life evaluation, emotional health, physical health, healthy behavior, work environment and basic access — all of which is said to contribute to the happiness of an individual. A reader of the article may be interested to learn what makes a state happy. As an investigation, the authors compared the happiness scores with median state incomes. The scatterplot shows the ‘possible’ positive relationship between a state’s median household income (in x-axis) and its well-being (y-axis). There are 50 dots in the plot.
- The scatter plot
- [Activity] Evaluating visualization is not easy!
- [Activity] Peer-review of data visualizations
- Data representations and transformations for designing network diagrams
- Skim through the assignment questions on network visualization
- Skim through the assignment questions on evaluating visualizations
- Submit your one-minute paper
Watching assignments:
Assignments:
- Several tasks to evaluate data visualizations
- Several tasks to design network visualizations
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
11/28 - Mapping data
Learning objectives:
- Understand why most map projections are wrong
- Designing effective choropleth maps
Classroom agenda:
- Attendance
- Slides
- Discuss the assignment questions
- Demo of using Flourish Studio for creating world choropleths
- Submit your one-minute paper
Reading assignments:
- TTA’s Chapter 10 - Mapping data
Assignments:
- Several tasks on mapping data
- Improving your UMSL data graphic
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
- Contents from the slides including the contents of the Youtube video within the slides.
12/05 - Presenting and Story telling
Learning objectives:
- Analytical practices for displaying links and causal arrows
- Smarter presentations and shorter meetings
- Storytelling: The next step for visualization
Classroom agenda:
Reading assignments:
Assignments:
- Several non-visualization tasks
Additional reading assignments for graduate students: (for writing a summary)
Topics for quiz (next week):
12/17 - Semi-comprehensive final (contents after the mid-term)
