Customizing Quarto reports and presentations
Lecture 24
2024-06-18
Before we get started
Go to your
aerepo, and pull.Make a change, any change, to
ae-18-second-to-last-ae.qmd. render, commit, and push.
Project presentations on Monday! 🥳
Do not discuss the take home exam if you meet to work on the project. Please keep the Duke Community Standard in mind.
Make sure your presentation is pushed to your GitHub repo before your lab section.
Get to lab on time, 5 minutes prior if possible – all team members must be present in class and take part in the presentation + Q&A
Find out your presentation order when you get there.
Deliver your 5-minute presentation
Answer questions during your own Q&A or ask questions to others. Participation will be noted.
Project write-ups due 6/25 at 11:59 PM
There’s a good chance you’ll be done with these on Monday as well.
But you might want to improve your write-up based on inspiration from other teams’ presentations and/or ideas that came up during your Q&A.
There is no Gradescope submission, just push your final edits to GitHub.
For the final report, make sure you suppress warnings, suppress code, and render the document to pdf.
Complete the teammate evaluation quiz by 6/25 at 11:59 PM on Canvas.
Teammate evaluation feedback
Most everyone seems content with the group dynamics !!
One useful note from the survey- communicate with your teammates, even if you don’t have positive results. For example, if you can’t figure out how to do something, communicate this!
Questions from last time
Expectations
The goal of this project is for you to demonstrate proficiency in the techniques we have covered in this class (and beyond, if you like) and apply them to a novel dataset in a meaningful way.
Note
Beyond, if you like – “you” is the whole team!
Expectations
The goal is not to do an exhaustive data analysis i.e., do not calculate every statistic and procedure you have learned for every variable, but rather let me know that you are proficient at asking meaningful questions and answering them with results of data analysis, that you are proficient in using R, and that you are proficient at interpreting and presenting the results.
Requirements
Focus on methods that help you begin to answer your research questions. You do not have to apply every statistical procedure we learned.
Tip
Critique your own methods and provide suggestions for improving your analysis. Discuss issues pertaining to the reliability and validity of your data, and appropriateness of the statistical analysis.
Tip
You can critique the current research without talking about a hypothetical future research,.
How many plots
You do not need to visualize all of the data at once. A single high-quality visualization will receive a much higher grade than a large number of poor-quality visualizations.
Note
There is no specific, secret number of visualizations I’m expecting, the right number is the number that it takes to answer your question.
Submission
You will not be submitting anything on Gradescope for the project. Submission of these deliverables will happen on GitHub.
Writeup
- Is there any paper that is required as well as the presentation?
- What is the project write up?
- Are write ups usually around the 10 page limit?
- Is there a recommended outline to the project?
Something else 💛
I have enjoyed this semester, and I want to continue learning R. What classes do you recommend I take to continue my learning?
STA 323: Statistical computing - R as a programming language
STA 210: Regression analysis - for anyone interested in applications
STA 221: Regression analysis - for majors + minors + anyone interested in the theory as well as applications
Quarto demo / Code review recap
Your project write-up with Quarto
Figure sizing:
fig-width,fig-height, etc. in code chunks.Figure layout:
layout-ncolfor placing multiple figures in a chunk.Further control over figure layout with the patchwork package.
Chunk options around what makes it in your final report:
message,echo, etc.Citations.
Finalizing your report with
echo: false.
Course Eval
