Assignments

General

For the first few weeks of the course, there will be a short assignment every week. You are advised to start on these on Tuesday (whether we’ve said exactly what the assignment is by then or not). We will typically work on them or talk about them in class during the week. They are technically due Fri at 4:30 PM. This is to encourage you to finish quickly if you can, and move on with your life, not to give you pressure.

If your assignment will be late, please email us bio708qmee@gmail.com by Friday afternoon to let us know when you will hand it in. This should be before Monday at noon, unless we give permission for special circumstances.

The actual content of your assignment should be posted to your GitHub repo
Submit your assignment (i.e. tell us you have finished) by email to bio708qmee@gmail.com. Your assignment is not done until you do this. To submit an assignment:
Tell us the main file we should be looking at, including the relative path from the main repo directory, e.g, hw1/add.R
Other files that are relevant can simply be mentioned in the script, e.g.:

read.csv("eggplant_survey.csv")
## Plot the histotypes (see README.md)

Tell us what working directory you run the script from (this will typically be either the main repo directory, or the assignment directory)

For lots of opinions and thoughts on R coding style, see here

Policy on use of large language models

You are allowed to use generative AI/large language models (Claude, ChatGPT, Gemini, Copilot, etc. etc.) for any component of this course. However:

you are (of course) personally responsible for all material you submit (we will be extremely grumpy if we encounter weird code or writing that doesn’t seem to come from you …)
you must always cite GenAI use (see citation guide), including which LLM you used and what your prompts were
we strongly discourage you from overuse of LLMs, especially when you’re learning R or basic stats
- Ted Chiang says “Using ChatGPT to complete assignments is like bringing a forklift into the weight room; you will never improve your cognitive fitness that way.”
- Andrew Heiss’s “AI, LLMs,- BS, and Vibe Coding.” says
  
  If you know what you’re doing, and you mistrust everything the LLM spits out, and hand-check everything it says, vibe coding can save you some time. HOWEVER it is (1) potentially dangerous, and (2) bad for learning.
of course, these guidelines (citation, personal responsibility) apply to material taken from Stack Overflow or other forums

Weights and rubrics

Regular assignments will be marked on a scale of 0-3
- 0: not submitted
- 1: sub-standard, definitely try harder
- 2: fine, fulfils expectations (equivalent to an A grade)
- 3: excellent (A+)
Assessments will be weighted as follows
- participation (forum and in-class) 10%
- assignments 45%
- first draft of project 15%
- in-class presentation of final project 15%
- written final project 15% (you will get feedback and have a chance to make improvements between the presentation and the final submission of the written project)