Communicating data science results effectively

Lecture 23

Dr. Mine Çetinkaya-Rundel

Duke University
STA 199 - Spring 2024

2024-04-17

Warm up

Any questions about the project?

My office hours this week: Office hours today 1:30 - 2:30 pm today
Remaining due dates:
- Project presentations next Monday in lab – all team members must be present.
- Project write-up and final repo due 8 am Wed, April 24 (you get an extra day!) – you will lose access to your repo at this time.
- Remaining application exercises due on the usual schedule.

Put any additional time into your project, MUCH HIGHER return on investment than any extra credit I can offer
But… AEs in class on Thursday and next Tuesday will be just you checking in saying you’re here. You’ll get to practice pull, commit, render, push, but no real content needed. So that’s two AEs you can get credit for simply by being here and doing no additional work than pull, commit (a tiny change), render, push during class.

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 meting between today and your presentation to practice your presentation together.

Any project questions?

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”)