Stat 220 Course Policies

Academic Integrity

  • Collaboration: Permitted for conceptual discussion only. All R codes and homework solutions must be independently created.
  • Resources: Use of Carleton faculty, peers, and approved materials encouraged. Unauthorized aids are prohibited.
  • Violations: Sharing or receiving .Rmd files, copying code, or uncredited collaboration is against the honor code.

Assignment Submission

  • Via GitHub: Submit organized and complete assignments according to homework guidelines.
  • Via Moodle and Gradescope: Submit the completed repositories in Github to Gradescope for grading purposes.
  • Content and Format:
    • Analyze and explain in complete sentences before any R code.
    • Include sequential, commented R code with relevant outputs.
    • Acknowledge any classmates consulted at the assignment’s start.

Late Work Policy

  • Homework:
    • One penalty-free late submission allowed per term.
    • For lateness beyond two hours, complete the Late Assignment Form.
  • Projects and Exams: Generally not accepted late, with exceptions considered on a case-by-case basis.

AI Policy

  • Use of Generative AI: Encouraged for learning enhancement with restrictions. Direct inclusion in assignments requires explicit approval.
  • Original Work: Essential. AI contributions must be disclosed.

Remember, the integrity of your work and understanding of data science principles are paramount in Stat 220. Adhering to these policies ensures a fair and enriching learning experience for all.