Exam 01

Exam
Modified

March 6, 2024

Overview

The exam will be released on Friday, March 15 at 8am and must be completed by Monday, March 18 at 11:59pm. There will be a fifteen-minute grace period for students who wait until the last minute to render their files and submit on Gradescope. Any submissions received after 12:14am will receive an automatic 20% deduction. Submissions will not be accepted after 11:59pm on March 19.

The exam will cover all techniques taught thus far in the class. It will consist of data analysis in R/RStudio and be submitted via Gradescope (like a usual lab or homework.)

Academic Integrity

  1. A student shall in no way misrepresent his or her work.
  2. A student shall in no way fraudulently or unfairly advance his or her academic position.
  3. A student shall refuse to be a party to another student’s failure to maintain academic integrity.
  4. A student shall not in any other manner violate the principle of academic integrity.

Rules & Notes

  • This is an individual assignment. Everything in your repository is for your eyes only.
  • You may not collaborate or communicate anything about this exam to anyone except the instructor. For example, you may not communicate with other students, other TAs, or post/solicit help on the internet, email, or via any other method of communication.
  • The exam is open-book, open-note, so you may use any materials from class as you take the exam. You may make use of online resources (e.g. package documentation, StackOverflow, Google search results) for coding examples on the exam. You may not directly copy and paste from these sources, but instead you need to adapt the code to fit your specific task. You must explicitly cite where you obtained the code using a code comment # immediately near the appearance of the reused code in the file. Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism.
  • You are permitted to use generative AI (GAI) for reference purposes only. You are prohibited from using GAI to write significant portions of code and/or analysis for this assignment. For example, you may not upload your data file to a GAI platform and ask it to create charts and statistical models for you.
  • Clarification questions may be sent to the course email account (info2950@cornell.edu) only. You may not email the TAs questions about the exam.

Submission

  • You must submit a PDF to Gradescope that corresponds to the .qmd file on your GitHub repository.
  • You must upload a PDF file. Any non-PDF submissions will not be graded.
  • Your PDF must be the rendered PDF generated by Quarto. Any PDFs generated by other means will not be graded.
  • We only evaluate code that is actually run. If you need to comment out code that is broken in order to render the PDF, you may do so but you will not earn credit for any code that has not been run.
  • Mark the pages associated with each question. If any answer for a question spans multiple pages, mark all associated pages.
  • Failure to mark the pages in Gradescope will result in lost points. Only pages that are marked will be graded and eligible to receive credit.
  • Make sure that your uploaded PDF document matches your .qmd and the PDF in your GitHub repository exactly. Your PDF should be fully reproducible from the .qmd file.

Grading

  • Total: 50 points