Due: 23 February, 11:59 pm

Weight: This assignment is worth 0.5% of your final grade.

Purpose: The purpose of this assignment is to learn some of the technical details of how to create charts for comparing values to one another and / or to a benchmark.

Assessment: This assignment is graded using a check system:

  • ✔+ (110%): Reflection shows phenomenal thought and engagement with the course content. I will not assign these often.
  • ✔ (100%): Reflection is thoughtful, well-written, and shows engagement with the course content. This is the expected level of performance.
  • ✔− (50%): Reflection is hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.

Notice that this is essentially a pass/fail or completion-based system. I’m not grading your writing ability, I’m not counting the exact number of words you write, and I’m not looking for encyclopedic citations of every single reading to prove that you did indeed read everything. I’m looking for thoughtful engagement, that’s all. Do good work and you’ll get a ✓.


  1. Read: Open up a notebook (physical, digital…whatever you take notes in best), and take notes while you go through the readings below.

  2. Reflection: When you have completed all of the readings, download and edit this template to write a ~150 word (or more) reflection about on what you’ve read (be sure to edit the YAML at the top). That’s fairly short - there are ~250 words on a typical double-spaced page in Microsoft Word (500 when single-spaced). You can do a lot of different things with this memo, for example:

    • Discuss something you learned from the course content
    • Write about the best or worst data visualization you saw recently
    • Connect the course content to your own work
    • Discuss some of the key insights or things you found interesting in the readings
  3. Make a Chart: Once you’ve read through everything, add a code chunk in your reflection that creates one of the charts you saw in one of the readings. Cite the source of the chart. The goal is to try and reproduce the chart as closely as possible to how it looks in the reading, so it is perfectly fine to copy-paste code directly into your reflection. You may need to modify the figure dimensions in the chunk settings.

  4. Submit Everything: Knit your document to a html page, then create a zip file of everything in your R Project folder. Go to the “Assignment Submission” page on Blackboard and submit your zip file.


“At the heart of quantitative reasoning is a single question: Compared to what?”

– Edward Tufte

Most of the readings this week have code in them that illustrate how to create each chart type, and I encourage you to try and reproduce the examples provided in R yourself. You may also want to take a look at the top 50 ggplots, which contains examples with ggplot code to create 50 common visualizations.

Plot types for comparing values:

Optional reading:

P.S. Since nobody found the easter egg in Mini Project 1, anyone who finds it between now and class on 2/24 will get an extra 10% on Quiz 2 (if you find it, send me a message on Slack describing what you found and how you found it)

EMSE 4575: Exploratory Data Analysis (Spring 2021)
Wednesdays | 12:45 - 3:15 PM | Dr. John Paul Helveston | jph@gwu.edu |