README for Group Assignment 1.5

CEGM1000 MUDE: Week 1.5, Friday, Oct 4, 2024.

You can access this assignment with the following link: classroom.github.com/a/6VU2xhZR.

GA 1.5 focuses on fundamentals of numerical analysis.

There are several files to be aware of:

1. README.md
2. Analysis.ipynb
3. Report.md
4. justIce.csv

As before, you should complete the analysis in Analysis.ipynb then answer the questions in Report.md.

Working Method

1. Clone the repository
2. Work with your group members to complete the tasks in the notebook.
3. Use VS Code LiveShare to quickly share code from one computer to another, or update the Report. Do not view and edit it very actively with all members simultaneously.
4. Keep track of who is working on each file to avoid merge conflicts, which take up valuable time. Don't try to merge notebooks; instead have one person work on them at a time and make a commit. If a second person is working on the notebook, use LiveShare to share code, or wait until a commit is pushed, then pull the commit to your computer and make your changes.
5. Remember to leave time at the end of the session to merge all branches, push all commits and sort out any issues that may arise.

Your repository does not have an automatic Actions check. Just confirm that your notebook and report have been uploaded.

Grading and Feedback

The grading and feedback system in previous works has failed, and we apologize for the delay. Starting this week the grading for GA's will be as described here.

The grade for this assignment will be determined by evaluating the overall quality of all questions in the report, as well as confirming that you complete the tasks in the notebook.information. A number of 0, 3, 6, 7.5, 9 or 10 will be assigned, along with a feedback document containing general comments about the GA results. You will be able to use this feedback and your score to help see where your GA could have been improved, as well as study for the exam.

Examples illustrating how the grades will be assigned:

• 10 points: exceptional.
• 9 points: excellent, but of course there is always room for improvement.
• 7.5 points: good, but some of the answers are incorrect or do not provide sufficient quantitative information. Answers cover the concepts well but are limited in terms of application or relevance to the problem at hand and are not adapted from the information and context provided in the textbook.
• 6.0 points: sufficient, as there are many of the issues described in the previous item, or significant problems with the implemetnation.
• 3.0 points: insufficient.
• 0.0 points: no submission, or submissions with negligible apparent effort.

As before, quality (and being quantitative) is much more important than being quantity.

End of file.