How-To: Make an Assignment Attempt#

As noted in the syllabus, each assignment will consist of two parts: an attempt and then completion of the assignment. The assignment attempt will be discussed here in a bit more detail.

The central idea behind these two phases is that you are incentivized to plan your time so that you don’t find that you have no idea what’s going on the night before the assignment is due.

Assignment attempts are generally due one week after we have started a module. Individual due dates can be found in the assignments tab, although these may change somewhat as we move through the course.

The attempt should consist of a Jupyter notebook or PDF containing either your solution, an attempted solution (even one that’s wrong!), or thoughts on how you will solve each part of each problem in an assignment. The attempts need to clearly indicate what sub-problem you are attempting!

We will grade these holistically, using the +/✓/- system, based on the fraction of assignment problems that have acceptable attempts. Receiving a + corresponds to “exceeds expectations” and will be converted into full marks in the grade book, a ✓ can be thought of as “meets expectations”, or partial marks, and a - means that the attempt did not meet expectations, yielding low marks. Our “expectations” in this context are that an acceptable attempt has been provided for most of the subproblems in an assignment. Again, this will be half of your assignment grade, so bearing with the process is worth it!

Since this is likely not something you’ve seen in previous classes, we will provide a descriptions of acceptable and unacceptable attempts below. Also here is a sample attempt based on Worksheet 1.1 indicating acceptable and unacceptable attempts and why they are marked that way.

Acceptable attempts:#

  • Completed solution to the sub-problem.

  • Partially working solution with a note on what remains to be done

  • A pseudocode outline of a solution with a note on how this will solve the problem

  • An outline in English of a solution

  • Links or references to the course notes, worksheets, videos, or outside resources indicating where you will look for help with a solution.

  • Questions or comments on the problem, indicating what you don’t understand, such as specific terms, concepts, or coding techniques. (These should be asked on the discussion board or in office hours!)

  • A plan to solve the problem via research, study, and asking questions. The plan indicates that it is targeted at the specific sub-problem.

Unacceptable attempts:#

  • Vague questions/statements that don’t reference the problem:

    • “I’ll google it” (Acceptable: “I plan to Google ‘Poisson distributions in Python’ so that I can learn how to make the random numbers for this problem”)

    • “I’ll look in the course notes” (Acceptable: “I plan to look in the notes for the KS-test and the associated worksheet because I don’t know how to perform that test yet.”)

    • “I’ll ask in office hours” (Acceptable: “I am stuck on what an empirical CDF means, so I’m going to ask someone to expand on that in office hours.”)

  • “I don’t even know what the problem is asking” (If this is ever truly the case, please send us an email!)

  • Code that is not obviously related to the problem

  • Non-answers.