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Class Overview
Contemporary research in higher education (and other disciplines) should be both rigorous and reproducible. This is class will teach you the fundamentals of data management and quantitative research workflow with emphasis on rigor and reproducibility.
Often referred to informally as “the R class”, you will get an introduction to coding using the R programming language, but many of the skills are directly transferable to future work in Python, Stata, or other software.
Credit to Dr. Skinner
First and foremost, credit for the structure and vast majority of the content on this site goes to Dr. Benjamin T. Skinner who designed this course before leaving UF to take a data scientist position at the National Endowment for the Humanities. I took this class with Dr. Skinner in Spring 2022, then was a Teaching Assistant for this class with him during Spring 2023. In building this class website, I’ve tried to keep the majority of the content consistent whilst making the class work for the format Dr. Tanner and I are going to teach it in.
If you’re interested in seeing Dr. Skinner’s versions of the class, here are links to his course site
A Note on “Uncertainty Tolerance”
One of my close friends is full-time application developer for UF, and he likes to talk with his new hires about the need for “uncertainty tolerance”. In essence, this is the ability to be okay with not knowing if something is going to work as expected and having the patience to play around until it does. For some, this comes naturally, for others this is one of the biggest hurdles to overcome. Unfortunately, whichever category you fall into, to learn to code you will need to build up some level of “uncertainty tolerance”. There are going to be times you code doesn’t run or work as expected, and every single programmer I know solves these issues the same way, playing around until it works. At first this may be wildly frustrating, particularly for some of you, but it will come over time, just bear with it as best as you can!
The “I’m Stuck” Workflow
- Take a break, go outside, get some food
- Talk to your rubber duck
- Talk to your classmates
- Please acknowledge with a
## h/t
- Please acknowledge with a
- Try Google or Stack Overflow
- Please acknowledge with a
## h/t(it helps you later too!) - Caution: the internet does strange things to people… Sometimes people offering “help” can be unnecessarily blunt and/or mean, particularly to people just starting out
- Please acknowledge with a
- Matt’s office hours or email
- Trying the above steps first really helps me help you
- I’d probably start by going through them anyway
- I rarely will give direct answers, I just help you think through the issue
- Trying the above steps first really helps me help you
Note: As one of the main purposes of this class is to teach you the basics of R programming, the use of AI-based coding tools (such as ChatGPT, GitHub Co-Pilot, Google Bard, etc.) is not permitted.
Useful RStudio Keyboard Shortcuts
- Run selected code: Command Return (mac) Ctrl Enter (windows)
- Comment/un-comment selected lines: Shift Command C (mac) Ctrl Shift C (windows)
- Auto-format code indentations: Command I (mac) Ctrl I (windows)
- New code chunk (in .qmd files): Option Command I (mac) Ctrl Alt I
- Toggle full screen code window: Control Shift 1 (mac) Ctrl Shift 1 (windows)
- Multi-line cursor: Alt then Drag-the-mouse
- Typical shortcuts such as Command/Ctrl C for copy also work
See more here
Useful Links
Good luck in the class!
