Final project

For your final project, you will do some data analysis and produce a piece of “data communication.” This communication must include some data visualization, and one or the other of writing about data or speaking about data.

You have three deliverables for the project:

1. The data communication. I imagine this will be one of the following:
   • A knitted HTML document with words and visualizations
   • A slide deck created using PowerPoint, Keynote, etc
   • A PDF document either knitted from Rmd or created from a Word document
   • Something else?? I’m really flexible here, so if you have a vision for something different, just run it by me. I guess you could do a YouTube video pr TikTok or something?
2. A “behind the scenes” process document. If you’re working in R, this will just be the Rmd document that got knitted into the final HTML or PDF. If you used a spreadsheet or other software, I would like a document outlining the steps you took to clean and wrangle your data.
3. A meta-description of the project.
   • Why did you choose the topic you did?
   • What is your intended audience? (E.g., the CEO of Uber, readers of the Star Tribune, people subscribed to the r/dataisbeautiful subreddit, etc. Your audience should not be “students in STAT 336” or “Dr. McNamara.”)
   • How did you find the data?
   • Why did you make the design decisions you did? (E.g., color choices in a visualization, specific language in a written piece, images on a PowerPoint slide.)

We’re living in a pandemic, and everything got pushed back during this semester. So, I’m not going to set any hard rules for length. If this was a regular semester, I would say the following:

• A talk should be at least 5 minutes long
• A piece of writing should be at least 1000 words
• The meta-document should be at least 500 words

For this semester, shorter is fine.

When I’m grading, I’ll be looking mostly to see if your finished product looks finished, and whether it seems appropriate for the audience you describe in your meta-document. Here are some things I’ll consider:

• Titles and axis labels on plots. These should be polished, not the default variable names that ggplot2 sticks in when you don’t specify them
• Encoding choices. Did you stick with default colors, or make them more appropriate for your audience? Does the visualization you chose make sense for the data?
• Consistency across the product. If you have multiple visualizations, do they hang together? (E.g., are the color choices consistent across plots to allow you to make comparisons, or do they change seemingly without reason?) In a presentation, are the headings consistent across slides?
• Typos/copyediting. This goes for writing in a written piece or in a presentation, titles on graphs, etc. Remember, RStudio has spellcheck, you just need to click the green checkmark button!