Overview

Assignments

Problem sets

To practice working with data you will complete problem set assignments throughout the quarter. You will submit your assignments on Canvas.

Exams

  • Exams are multiple choice; you will need a RED scantron with 50+ response items
  • You are allowed one “cheat-sheet” on each exam (regular computer paper, front and back)
  • The midterm exam covers all content (lectures, videos, audio, etc.) up to the day of the exam
  • The final exam covers all content (lectures, videos, audio, etc.) between the midterm and the last day of class
  • Exams are in-person, in our regular classroom
  • There is no take-home or online option for either exam, and there are no scheduled make-up exams. The final exam cannot be taken early. Please plan your end-of-quarter travel accordingly

Grading

The course TAs are responsible for all grading. They are highly capable and knowledgeable. Concerns about grading should be directed to your TA. Any request for a re-grade must be made to your TA within one week of the assignment being returned to the class, and must be accompanied by a 500-word written justification for the request. Note that a re-grade may either raise, lower, or leave unchanged the original grade.

Extensions on take-home assignments

You can turn in the problem set one day late, no questions asked, though you will lose a full letter-grade. Beyond that I will not accept late assignments without a doctor’s note / formal letter of absence.

The rules

Honor Code

Be nice. Don’t cheat. The Code of Academic Conduct is in effect in this class and all others at the University. I will treat violations seriously. If you have doubts, it is your responsibility to ask about the Code’s application.

Plagiarism and AI

All submitted work will be filtered through TurnItIn’s plagiarism- and AI-detection software. Any submitted work that is not scannable by TurnItIn will receive zero credit. You are responsible for following university-prescribed guidelines on plagiarism, cheating, and use of AI. Note that any use of AI-generated content is considered academic misconduct. All cases of potential or actual misconduct will be immediately referred to Judicial Affairs. Ignorance of university guidelines is not an acceptable justification for academic dishonesty.

For more information, see the following resources:

  • https://ossja.ucdavis.edu/judicial-faqs
  • https://ossja.ucdavis.edu/code-academic-conduct
  • https://ossja.ucdavis.edu/avoiding-plagiarism-mastering-art-scholarship