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MACS 40700 - Data Visualization (Spring 2017)

Dr. Benjamin Soltoff
Email [email protected]
Office 249 Saieh Hall
Office Hours Th 2-4pm
GitHub bensoltoff
  • Meeting day/time: MW 1:30-2:50pm, Saieh Hall, Room 247
  • Office hours also available by appointment

Course description

Social scientists frequently wish to convey information to a broader audience in a cohesive and interpretable manner. Visualizations are an excellent method to summarize information and report analysis and conclusions in a compelling format. This course introduces the theory and applications of data visualization. Students will learn about theory of cognition and perception in order to understand how humans process and synthesize information in a visual medium, while also developing techniques and methods for generating rich, informative, and interactive visualizations for both data exploration and explanation. These techniques will be developed using software implementations in R and D3.

Prerequisites

Students are expected to have prior programming experience; this is not an introductory programming course and students without this experience will have significant difficulties keeping up with the material. Experience could come from completion of MACS 30500 - Computing for the Social Sciences, an alternative course on programming at UChicago or undergrad, or self-taught experience using either R or Python. Students should also be familiar with the Git version tracking system and be comfortable with the Git workflow (commit, push, pull, merge, etc.). Finally, some basic experience with probability/statistical theory (especially regression analysis) will be helpful, though not required.

Grades

Assignment Points
Assignment 1 15
Assignment 2 15
Assignment 3 15
Assignment 4 15
Final project 30
Participation 10
Total Points 100

Disability services

If you need any special accommodations, please provide us with a copy of your Accommodation Determination Letter (provided to you by the Student Disability Services office) as soon as possible so that you may discuss with me how your accommodations may be implemented in this course.

Readings

Readings for the course will come primarily from the following books, as well as an assortment of journal articles:

I recommend you purchase a copy of TA. R4DS and D3 are both available for free online, however you can also purchase a hard-copy if you prefer that medium. TA and FA are also available as ebooks through the UChicago library (follow the links above, authentication required).

Course schedule

Date Day Topic Due dates
Mar. 27 M Introduction to data visualization
Mar. 29 W Principles of data visualization
Apr. 3 M Design and evaluation
Apr. 5 W Grammar of graphics and ggplot2
Apr. 10 M Science, art, or somewhere inbetween Assignment 1
Apr. 12 W Exploratory data analysis
Apr. 17 M Graphical perception and cognition
Apr. 19 W Multivariate data visualization
Apr. 24 M Rules of thumb
Apr. 26 W Visualizing scientific results
Apr. 28 F Assignment 2
May 1 M Interactivity
May 3 W Interactivity (cont.)
May 8 M Geospatial visualization
May 10 W Introduction to D3 Assignment 3
May 15 M Network visualization
May 17 W More D3
May 22 M Text visualization
May 24 W Final project presentations Assignment 4 / Present final project
May 29 M No class (Memorial Day)
May 31 W Final project presentations Present final project
June 4 Su Submit final project

References and Readings

All readings are required unless otherwise noted. Adjustments can be made throughout the quarter; be sure to check this repository frequently to make sure you know all the assigned readings.

  1. Basic principles of visualization
    • TA Ch 1, 2, 5
  2. Simple charts
    • TA Ch 1, 2, 5
  3. Design and evaluation
  4. Grammar of graphics and ggplot2
  5. Science, art, or somewhere inbetween
  6. Exploratory data analysis
  7. Graphical perception and cognition
  8. Multivariate data visualization
    • TA Ch 8-9
  9. Rules of thumb
  10. Visualizing scientific results
  11. Interactivity
  12. Interactivity (cont.)
  13. Geospatial visualization
  14. Introduction to D3
    • Murray Ch 1-6
  15. Network visualization
  16. More D3
    • Murray Ch 7-13
  17. Text visualization
  18. Final project presentations
  19. No class (Memorial Day)
  20. Final project presentations

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