Course Meetings | Description and Objectives | Instructor | Prerequisites | Readings | Weekly Plan | Evaluation | Copyright | Accommodations | GWU Policies
Course Meetings
- Mondays, 3:30 to 5:20
- Monroe 114
- NOTE: Wednesday, December 9 is a “designated Monday” and is our last class
Course Description and Learning Goals
Course Purpose
Not all graphics are created equal: some lie, some obscure, some illuminate, and some compel. This course studies how to spot lies and obfuscation and teaches you how to illuminate and compel. In this class, we learn how to distill large quantities of data into pictures that communicate.
Ideally, policy choices are driven by information. Because of its ability to generalize across large populations, the most credible information is frequently quantitative. However, data alone tell no story. Without visualization, it is very difficult for data to influence policy. This course challenges you to take raw numbers and create a story that can change impressions, long-held beliefs and ultimately policy. Together, we learn to tell stories with numbers using graphics.
Learning Objectives
- Value high quality data graphics
- Present data to illustrate a narrative that influences policy
- Understand how visualizations can rapidly and accurately convey a large amount of quantitative data
- Follow the logic of technical software that creates data visualizations
- Implement your own programming logic
- Critically analyze data visualizations
- Work with big-ish datasets to produce summary analyses
- Use summary statistics -- from econometrics and research methods courses -- appropriately in producing graphics
- Recognize the limits of cognition of visually displayed data, and produce graphics that speak to the broadest possible audience
Instructor
Professor: Leah BrooksMedia and Public Affairs Building, Room 601F Office Hours: Wednesdays 10:30 am to 1 pm and 7:30 pm to 9:00 pm. Evening hours always on zoom. Daytime can be in person if you notify me sufficiently in advance.
- Use the scheduler to book a 15-minute slot
- If there are no other students waiting, I am happy to talk beyond the 15 minute limit
- Office hours are by Google Meet, unless you would prefer to meet in person. I can usually accommodate in-person meetings during daytime slots with advance notice.
- Your confirmation email from the scheduler will contain the Google Meet link
- No office hours Wednesday November 4.
lfbrooks at gwu.edu, but please use Piazza email for all non-private issues
Contact policy: I will do my best to answer emails within 24 hours during weekdays, or within 24 hours on the soonest weekday if you email on the weekend. If you do not hear from me within this time frame, you should assume that your email has been lost and you should re-send.
If you have missed a class, your first line of defense to ask what you have missed is another student.
Prerequisites
- I do not assume prior programming knowledge, either in R or any other statistical programming language.
- Because this class focuses on learning the basics of statistical programming, expect a greater time commitment if you have no prior programming experience.
Readings
Required Readings
See lectures tab for reading dates and specific pages. All readings should be on order at the bookstore.- Few, Stephen, Show Me the Numbers: Designing Tables and Graphs to Enlighten
- Chang, Winston, R Graphics Cookbook: Practical Recipes for Visualizing Data, Second Edition. Available online for free here
- Knaflic, Cole Nussbaumer Storytelling with Data
- Tufte, Edward, The Visual Display of Quantitative Information
- Manson, Steven. Mapping, Society and Technology, University of Minnesota, 2017.
Books are on order at the campus bookstore, and are widely available online. I have tried to link to all remaining content from this syllabus. Please let me know if you have difficulties with any of the links, or with permissions.
Supplemental Readings -- For Reference
- Lima, Manuel, Visual Complexity: Mapping Patterns of Information, available online at GW Library
- Learning R
- Schwabish, Jonathan, Better Presentations: A Guide for Scholars, Researchers and Wonks
- Schwabish, Better Data Visualizations: A Guide for Scholars, Researchers and Wonks, 2021.
- Other Data Visualization Courses
- Enrico Bertini
- Newman, Winifred E. Data Visualization for Design Thinking: Applied Mapping
- Brunsdon and Comber, An Introduction to R for Spatial Analysis and Mapping
- Healy, Kieran, Data Visualization: A Practical Introduction
- Brewer, Cynthia A., Designing Better Maps: A Guide for GIS Users
- Wilkinson, Leland, et al, The Grammar of Graphics . The intellectual inspiration for ggplot.
- W.E.B. DuBois Center, W.E.B. DuBois's Data Portraits: Visualizing Black America
- Alberto Cairo
- 2016: The Truthful Art
- 2020: How Charts Lie
- 2023: The Art of Insight: How Great Visualization Designers Think
Weekly Plan
Each week, the in-class lecture is half design principles and half R coding. I expect that you do the associated reading before arriving in class. In class, we will discuss the readings and the R lesson for the week. To recap,Before Class
- You read the assigned texts
- You do the assigned tutorial
- Shortly before class, I post the week's programming tutorial
- Short quiz on material from previous tutorial
- Administration overview
- Good, Bad and Ugly
- Answer questions from reading
- Present lecture on design principles and coding
- Discuss some coding examples
- Time permitting, you work on coding
Outside of class
- Use Piazza for coding questions
- Familiarize yourselves with features that show blocks of code
- Perhaps no longer as useful, but I keep in case you need it: Learn how to create a “minimal reproducible example” of your problem. See Stack Overflow's excellent description here
Assessment and Evaluation of Learning
- Weekly Programming Practice (30%)
- Creating data visualizations requires technical knowledge.
- These problem sets are designed to develop your R skills so you can successfully create the final project.
- You will begin these tasks in class each week; you need to finish them by the following class.
- I will evaluate what you learned from these tutorials via a quiz at the beginning of each class preceded by a tutorial.
- We have nine quizzes throughout the semester, and I will use your top five scores.
- No make-up quizzes for any reason.
- One Fully Composed Chart (5%)
- This assignment is a warm-up for your policy brief and a chance to get feedback before the policy brief.
- Lecture 5 you will turn in a fully-executed graph on the topic of your choice, along with the code in R.
- See further details in handout.
- I do not accept late assignments
- Visualizations: The Good, the Bad and the Ugly (5%)
- One of the goals of this course is for you to recognize quality data visualizations and misleading data visualizations.
- This will help you review and identify the strategies from the previous class, and will require you to explain the strengths and weaknesses of the graphics.
- To this end, one or two students each week will find a visualization that can be improved based on the previous week's class.
- We will post them on the course website and each student is responsible for bringing three specific discussion points on the graph for the beginning of class.
- We will make assignments for this activity the first class.
- No late assignments are accepted.
- Policy Brief (40%)
- A policy brief -- a version of a short memo -- is the primary method of policy communication. This assignment asks you to create such a memo.
- For our final class, you will turn in an approximately five to then page policy brief, with approximately eight data visualizations.
- This project includes interim steps described below.
- The goal of this exercise is for you to
- Connect what we've learned in course with policy
- Practice R
- Direct inquiry toward an unstructured project
- Challenge your newly developed visualization skills
- You are required to use micro data, in the sense that the data you load are less aggregated than (at least) some of the data you present.
- For relevant briefs, you are very welcome to post on the Center for Washington Area Studies page
- Logistics
- Paper is due the Monday following the final lecture.
- You are welcome, but not required, to work in pairs. Requirements do not differ if you work in pairs; you should correctly interpret this as an incentive to work in pairs.
- Extensions will be given only in the case of illness
- Briefs will be graded out of 100 points
- Any essays submitted late will decline by ten points for each twelve hours the essay is late, e.g. if the essay is due on Friday and is received Monday, if it would have received 70%, it now receives 10%
- Interim Assignments for Policy Brief (total of 15%)
- Policy Brief Proposal (5%)
- To make sure that you have chosen a manageable assignment, on week 3 you will turn in a description of what you are planning to visualize
- This should be one page or less. It should identify your data source(s), and outline what you'd like to say.
- I will provide written feedback on your proposal within one week of submission.
- I will comment on, but not give credit for, late work
- In-class Storyboarding Workshop (0%)
- Week 7 you will work together with your classmates to tell a story with your findings
- Policy Brief Workshop (5%)
- To make sure that you are on track to complete a high-quality policy brief at the end of the semester, and to hone your critical visualization skills, on week 9 you will produce a draft of your policy brief for peer feedback.
- Specifically, you will post a draft of your policy brief, complete with draft visualizations, and give and receive feedback on these visualizations.
- We will work in small groups that I will assign, and you comment on your group members' work
- I will provide more details in a handout in week 7
- Policy Brief Presentations (5%)
- We use classes 13 and 14 for presentations of your policy briefs
- Half of your grade will be based on your comments on your classmates' presentations (2.5%)
- Half of your grade will be based on your presentation (2.5%)
- I will provide more details for this activity closer to the date.
- No late work is accepted
- Class Participation (5%)
- To make sure you're up to date with the reading -- which should help you understand the creation of good graphics -- I will ask questions of all students in each class.
- Come prepared to answer questions
Course Material Copyright
Course materials posted on this website, Piazza, or elsewhere are intellectual property belonging to the author. Students are not permitted to buy or sell any course materials without the express permission of the instructor. Such unauthorized behavior constitutes academic misconduct.
Accommodations
We want to provide an environment that helps every student in this course succeed. If you have accommodations of which the instructor should be aware, please inform the instructor no later than the first week of the course so we can plan together for a successful semester. In order to receive accommodations on the basis of disability, you'll need to provide proper documentation to the Office of Disability Support Services, Marvin Center 436, 202-994-8250. We accommodate students based on the recommendations of the DSS Office.GWU Policies
University Policies
University policies are located here.Out of Class Learning: Average minimum amount of independent, out-of-class, learning expected per week: In a 15 week semester, including exam week, students are expected to spend a minimum of 100 minutes of out-of-class work for every 50 minutes of direct instruction, for a minimum total of 2.5 hours a week.
With many thanks to Bobby Kleinberg, from whom this webpage borrows liberally.