Data Visualization

Course Logistics

Mondays, 3:30 to 5:20

When online: See zoom link in email
When in person: Bell 109
NOTE: Wednesday, April 27 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
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

Contact and Office Hours

Professor: Leah Brooks

Media and Public Affairs Building, Room 601F
Office Hours: Tuesdays, 10:30 am to 1 pm
Thursdays, 8:00 to 9:15 (last appt ends at 9:30 pm)
Use the scheduler to book these times.
Office hours are online until further notice; evening office hours will always be online.
lfbrooks at gwu.edu

Contact policy: Send programming-related questions and course administration questions relevant to all students to piazza. Send any private issues to my GW email. On both platforms, 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.

Teaching Assistant: Bianca Onwukwe

Office Hours: Fridays 7 to 9 pm, and weekends by appointment.
Connection information TBD.
BiancaOnwukwe at gwu.edu.
Phone number on Piazza.

Contact policy: Will respond to email (please send all programming questions to Piazza) within 24 hours on the soonest weekday.

More Teaching Assistance: Stephanie Palmer

Office Hours: Thursdays, 7 to 9 pm
See link in Piazza email.
spalmer1496 at gwu.edu

Contact policy: Sign up in advance for office hours here. Please sign up by 5 PM on Thursday, the day the Extra Help Session is held, to guarantee that Steph will be present to assist you. If you do not sign up by 5 PM, it is not guaranteed that Steph will be available to help.

Prerequisites

PPPA 6013: Econometrics for Policy Research I

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.

Few, Stephen, Show Me the Numbers: Designing Tables and Graphs to Enlighten
*R Graphics Cookbook: Practical Recipies for Visualizing Data. Also available online for free here
*Knaflic, Cole Nussbaumer Storytelling with Data
Mulbrandon, Catherine, An Illustrated Guide to Income in the United States
Tufte, Edward, The Visual Display of Quantitative Information
Monmonier, Mark How to Lie with Maps, any edition is fine.
Monmonier, Mark Mapping it Out: Expository Cartography for the Humanities and Social Sciences

Books marked with a * are available online at the GW library.
See full details with chapter and dates on readings tab.

These 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
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 Visualiation: A Practical Introduction
Brewer, Cynthia A., Designing Better Maps: A Guide for GIS Users
Wilkinson, Leland, et al, The Grammar of Graphics
W.E.B. DuBois Center, W.E.B. DuBois's Data Portraits: Visualizing Black America

Weekly Plan When Online

To better work with the online format, for weeks when the class is online, I will pre-record half of the lecture. In each week, the lecture is half design principles and half R coding. I will alternate which part of the lecture I record. Regardless, I expect you to do the associated reading and listen to the lecture before arriving in class. In class, we will discuss your questions from the online lecture and I will ask you questions about the assigned journal article. To recap,
Before Class

Wednesday before class, by midnight, I post lecture videos for the following week's lecture (first lecture posted 1/6)
You read the assigned texts and watch the lecture video
Shortly before class, I post the week's programming tutorial

During Class

Administration overview
Good, Bad and Ugly
Reading quiz
Answer questions from online lecture or reading
Present lecture for un-recorded portion
You work on coding

I anticipate that in most weeks we will use less than the full class time. My goal is to have class last about 70 minutes as a standard lecture. The remaining 40 minutes you should work on the tutorial, while I stay online to provide advice as needed.
Online Expectations

Generally, I expect you to have your camera on during class sessions. This helps me understand when explanations are lacking and creates accountability. While everyone may not always be able to do this, and I understand, camera on is the preferred option.
By default, mute yourself.
Raise your hand to ask questions. If the instructor doesn't see your hand, unmute and speak up.

Outside of class

Use Piazza for coding questions
Familiarize yourselves with features that show blocks of code
Learn how to create a “minimal reproducible example” of your problem. See Stack Overflow's excellent description here

Weekly Plan When In Person

When in person, I will not pre-record lectures. 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
Shortly before class, I post the week's programming tutorial

During Class

Administration overview
Good, Bad and Ugly
Answer questions from reading
Present lecture on design principles and coding
You work on coding

I aim to end class 20 to 30 minutes before 5:20. I encourage you to use this remaining time to start on the tutorial so that I can help with problems as they arise. I will always stay until 5:20 to answer any remaining questions or provide programming help.
Outside of class

Use Piazza for coding questions
Familiarize yourselves with features that show blocks of code
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 to turn in on paper in class and online at the beginning of class.
- Logistics
- Grading for this assignment depends on our TA status, which remains up in the air. I will update when I know.l
- Work with others on these assignments. Whatever you turn in, however, needs to be in your own words; no work should directly duplicate classmates' work.
- I accept no late assignments
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, 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.

Reading Quiz (5%)

We have reading quizzes only in weeks when class is online. I rescale the value of this component in your grade by the number of weeks we are online. For in-person weeks, this grading weight goes to the weekly programming practice.
At the beginning lecture, we will have a three-question quiz on the readings and recorded lecture for that class.
I will count the best 70 percent of your reading quizzes (best 7 out of 10 if we are online all weeks).
No late assignments or make-up work.

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 page policy brief, with approximately five data visualizations.
- This project includes interim steps described below.
- The goal of this exercise is for you to
- 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
Interim Assignments for Policy Brief (total of 10%)

Policy Brief Proposal (2.5%)

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
This will be an in-class (synchronous) activity

Policy Brief Workshop (2.5%)

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
You will make presentation videos, and we'll use class time for responses, probably divided in groups.
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

Trachtenberg School Course Policies

The Syllabus
This syllabus is your guide to the course. If any questions arise, please check the syllabus before contacting me or the TA. Sound educational practice requires flexibility and I may revise content and requirements during the semester.
Late or Missed Class
If you are late or absent from class, it is your responsibility to obtain all announcements, assignments, and handouts from this website or from your classmates. As participation is part of your grade, and because attendance in class helps you learn, missing many classes will be detrimental to your final grade. Missing one class should have no effect. You do not need to notify me in advance if you are going to miss class.
Exam Dates
Please notify me in the first two weeks of class if you are aware of a pre-existing conflict, such as a religious holiday you observe, that will preclude you from taking either exam at the assigned time. To the extent possible, we will work together to reschedule the exam as close to the original date as possible.
Submission of Written Work Products Outside of the Classroom
It is your responsibility to ensure that I receive your assignment on time. It is not permissible to submit assignments digitally unless I indicate so.
Collaboration on Assignments
You are welcome to work in groups; however, you are expected to write up your answers individually. This means that no phrases on your assignment should mimic phrases on any other student's work.
Submission of Written Work Products after Due Date
All work must be submitted by the assigned due date in order to receive full credit. Only extreme circumstances warrant exceptions. Late assignments will be marked down for each day that they are late.
Academic Honesty
All examinations and other graded work products are to be completed in conformance with the George Washington University Code of Academic Integrity. Note especially the definition of plagiarism: “intentionally representing the words, ideas, or sequence of ideas of another as one's own in any academic exercise; failure to attribute any of the following: quotations, paraphrases, or borrowed information.”
Incompletes
You must consult with me to obtain an incomplete no later than the last day of classes in the semester. At that time, we will both sign the CCAS contract for incompletes and submit a copy to the School Director. Please consult the TSPPPA Student Handbook or visit this link for the complete CCAS policy on incompletes.
Changing Grades After Completion of Course
No changes can be made in grades after the conclusion of the semester, other than in cases of clerical error.
Accommodation for Students with Disabilities
If you need extra time on exams or assignments due to a disability, let me know in the first week of class. 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. Accommodations will be made based upon the recommendations of the DSS Office.
University Counseling Center
The University Counseling Center (UCC), 202-994-5300, offers 24/7 assistance and referral to address students' personal, social, career, and study skills problems. Services for students include: crisis and emergency mental health consultations; confidential assessment, counseling services (individual and small group), and referrals
Religious Holidays
If you need to miss a class to observe a religious holiday, please notify me the first week of classes about any conflict; we will arrange an absence without penality.
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.
Title IX Information