Abbreviated Syllabus

Note: this is an abbreviated syllabus. The full syllabus is available through Classmate and/or Canvas.

Instructor Information

Meeting Times and Location

  • MW 1:00 pm-2:15 pm in 79/171
  • TR 9:30 am-10:45 am in 4/305

Office Hours

  • Monday: 9:00 am-11:00 am
  • Tuesday: 2:00 pm-4:00 pm
  • Wednesday: 9:00 am-11:00 am
  • Other times by appointment

Grading and Evaluation

The course grade will be determined as follows:

  1. R labs (25%): Students will complete in-class activities using Quarto and R. The resulting .html file should be submitted to the designated Assignment on Canvas by 11:59 pm on the specified date (see Canvas calendar).
  2. Weekly quizzes (10%): Once a week, students will complete a brief quiz at the end of class. Quizzes cannot be taken early and missed quizzes cannot be made up. Of the 13 planned quizzes, the lowest 2 grades will be dropped.
  3. Projects (40%): Every module will finish with a project to demonstrate the knowledge gained. These will be like the R Labs, but putting everything in the module together. The resulting .html file should be submitted to the designated Assignment on Canvas by 11:59 pm on the specified date (see Canvas).
  4. Final Exam (25%): The final exam will be a concepts-based written exam. While there may be some basic calculations needed, you will not be processing raw data.

It is expected that all work submitted is the student’s own work. Evidence of academic dishonesty, including use of “homework help” websites (e.g., Chegg) and copying other students’ work, will be submitted to the Dean of Students. A grade of 0 will automatically be assigned for the assignment and there will be no opportunities to change that grade. If there are repeated incidents, the sanctions attached will increase in severity, including an F in the course and suspension from the university.

What about AI? Absolutely okay when it’s used as a learning tool. It can be helpful when you are stuck, when you want to check your own work, asking for additional examples, or alternative explanations to concepts. However, it is not okay to let AI complete assignments for you.

Here’s how you can use AI responsibly:

  • Ask it to explain concepts you don’t fully understand.
  • Have it help debug your code and ask for help understanding R error messages.
  • Ask it to provide additional examples, perhaps in an area you are interested in.

Late Policy

All projects have due dates, however, the Assignments on Canvas will not close until the end of the semester. All students are automatically granted “extensions” without question.

Note that if there is not a submission when I go to grade (after the initial deadline), I will assign a zero (0) and request that you submit the assignment when you are able to. This is only for record keeping purposes. There is no penalty for submitting late and a full grade will be given upon review of your submission.

Extensions are not available for quizzes or the final exam. All work must be submitted by 8 am on December 14, 2025.