Communicating data science results effectively

Lecture 23

2024-06-18

Announcements

  • No Thursday office hours
  • Teammate evaluation 1 for your group project is due tonight by 11:59 PM. It is under the Quiz tab on Canvas. There will be time allotted at the end of class. This will be used, along with other factors, to determine your Teamwork score for the project.
  • A second teammate evaluation is due by 6/25 at 11:59 PM.

Take-home exam 2 tips

  • Make sure your take-home exam can render!
  • To be extra cautious: render every time after starting a new code chunk!
  • If you aren’t sure how to complete a problem, break it into sub-steps that you do know how to complete.
  • Reference the AEs! Solutions are on the course website next to the green check marks.

Project Write-up Tips

The final report should be nicely formatted as a formal summary of your data analysis.

  • Any math notation should be properly formatted in mathmode.
  • Only include figures that are pertinent to your analysis.
  • Do not include the URL for the data in the report. This should go in a formal References section.
  • Do not glimpse() the data in the final report.
  • No code should be printed to screen, but the project should be reproducible! For example, set seeds if you use randomization.
  • Please read all documentation on the course website regarding the project. It is all contained under the Project tab.

Options you MUST add to the YAML of report.qmd

  • To suppress warnings, to suppress the code, and to render your document to pdf:

Project

  • After Thursday, review peer evaluations left by your peers, implement updates as you see fit, close the issue once you review them.

  • Have a clear plan for who is doing what, open issues on your repo, and assign them to individuals who can then close the issues as they finish a task.

  • Schedule at least one team meeting between today and your presentation to practice your presentation together.

Any project questions?

Effective communication

Take A Sad Plot & Make It Better

Application exercise

Application exercise: ae-17-effective-dataviz

  • Go to your project called ae.
  • If there are any uncommitted files, commit them, and push. Then pull.
  • Work on ae-17-effective-dataviz.qmd.

Recap

  • Represent percentages as parts of a whole
  • Place variables representing time on the x-axis when possible
  • Pay attention to data types, e.g., represent time as time on a continuous scale, not years as levels of a categorical variable
  • Prefer direct labeling over legends
  • Use accessible colors
  • Use color to draw attention
  • Pick a purpose and label, color, annotate for that purpose
  • Communicate your main message directly in the plot labels
  • Simplify before you call it done (a.k.a. “Before you leave the house, look in the mirror and take one thing off”)

Reminders

  • Finish AE 16, exercise 12 and 13.
  • Finish AE 18.
  • Don’t forget to push AEs 16-18 to github.
  • Complete Teammate Evaluation 1 before 11:59 PM tonight.

To do before end of class

Meet with your team and,

  • Read the Milestone 2 feedback.
  • Decide on a data set and research question.
  • Make a plan for when you’ll meet to practice your presentation before 6/24.

🔗 sta199-summer24.github.io  ·  ❓ Ask on Ed