Requirements and Grading


There are two required textbooks for this course:

  • Angrist, J. & J. Pischke. (2015) “Mastering Metrics”. Princeton University Press.
  • James, G., D. Witten, T. Hastie, & R. Tibshirani. (2021) “An Introduction to Statistical Learning with Applications in R”. Springer. (Available online here)

All lecture slides, supplemental readings, course videos, and additional material will be provided on the course website.


I expect all students will attend each class, if they are feeling well. Attendance is the easiest way to learn the different topics that will be covered in class and ask questions. Even though I will not take attendance for every class, there will be some classes where attendance will be registered, and it will count towards your participation grade.

The attendance policy is designed in a lenient way to provide students with flexibility in case of any unexpected issue (including, but not limited to, sickness). All students can skip one class (with registered attendance) without excuses, and can make up for an additional absence through participation. Please read the grading section for more details on the specific policy. Recording of each class will be made available at the end of each week, but they are not a replacement for in-person attendance.


It is very important for students and all the instruction team to behave courteously and professionally. During class time, avoid outside distractions, and keep your focus on the lecture (texting/chatting or viewing other websites that are not related to the class is not permitted).

My main goal is to get students to be comfortable actively participating in class. Pairs/group discussions will be encouraged, and cold-calling will also be used to get students engaged.

I have a zero-tolerance policy for racist, sexist, xenophobic, homophobic, or any sort of disrespectful language or behavior towards anyone in this class, including other students, TAs, or the instructor. Any student violating this policy will be referred to the Dean’s office for disciplinary proceedings.


There will be one individual midterm and one final exam in this course. Additionally, there will be six homework assignments during the semester (only five will be counted), and Just in Time Teaching assignments (JITT) that should be completed before each class:

  1. Homework assignments: 35% (7% each, and you can drop one except for Homework 6)
  2. JITT assignments: 10%
  3. Attendance/Participation: 5%
  4. Midterm: 25%
  5. Final: 25%

I will use the cutoffs below to translate your overall course average into a final letter grade. These cutoffs are firm; we do not round course averages. So, for example, an overall course average of 89.99 is a B+, not an A-. I sometimes (but not always) curve grades for each assignment, but not for the final grade. There will be no extra credit, except for a small bonus for completing the course evaluation at the end of the semester.

Grade A A- B+ B B- C+ C C- D F
Cutoff 94% 90% 87% 84% 80% 77% 70% 65% 60% <60%

A note on copying and plagiarism
There is zero tolerance in this course for any academic misconduct, including copying or plagiarizing work from other sources (such as other students, internet sources, chatGPT, etc.). Students are allowed to use online resources for take-home assignments and are allowed to discuss the general approach to homework questions. However, copying code and/or answers that do not belong to the student is strictly prohibited. If there is evidence of misconduct, all students involved will be reported to the corresponding office and receive an according academic penalty in the class.

I now explain each of these grading components in more detail.

  1. Homework assignments (35%)
  • There will be six homework assignments in this course, with the following (suggested) submission deadlines:

    • HW1: September 8th, 11:59 PM
    • HW2: September 22nd, 11:59 PM
    • HW3: October 6th, 11:59 PM
    • HW4: November 3rd, 11:59 PM
    • HW5: November 17th, 11:59 PM
    • HW6: December 3rd, 11:59 PM This assignment cannot be dropped.
  • Homework assignments will be posted on Thursday, the week before they are due, so students will have over a week to complete the assignments.

  • Students are allowed to discuss homework assignments, but students are responsible for their own work and must be completed individually. Do not copy another student’s code or copy code from other internet sources without references. If any sign of impropriety is detected, the student will be asked to explain their answers/code in detail.

  • Homework assignments will be posted online and submitted through Canvas.

  • You must submit your homework write-up as a PDF, when required, as well as your R Script (or Rmarkdown file). Failure to submit your script will be considered as an incomplete homework. The code you submit with your homework should be fully reproducible (i.e. another person running it on their machine should be able to get the same results as you). See the guidelines on our course website for R scripts.

  • Only five homework assignments will be considered for your grade, dropping the assignment with the lowest grade, with the exeption of Homework 6. However, you can only drop an assignment for which you haven’t been penalized for misconduct.

  • There is a 10% penalty for each day your assignment is late. This penalty is to give everyone the same amount of time to submit their work. I recommend students plan ahead for the deadlines, so you don’t run out of time for on-time submission. If for any reason you cannot complete the homework in time, remember that you can always drop an assignment.

  1. Just in Time Teaching Assignments (10%)
  • Mini-assignments to be completed before class that should not take more than 15 minutes to complete. These might include questions related to the readings, watching a short video, or answering some questions related to the topics of this class. Additionally, it will include a knowledge-check for the previous class.

  • The objective of these assignments is for you to think about the topics that will be covered in class, motivate the discussion, and at the same time provide additional feedback for the instructor about where the students stand.

  • The knowledge-check portion of the JITT will be graded for correctness, but you can re-submit as many times as you want.

  • Questions related to next class material will not be graded for their correctness, but just for their completion. That being said, your submission should reflect that you tried to answer the questions appropriately (if not, your submission might not be counted).

  • JITT assignments need to be completed two days before class: Saturday 11:59pm for sections with class on Monday, and Monday 11:59pm for sections with class on Wednesday.

  • Make sure you submit your JITT by the deadline. All submissions made after the deadline will not be counted.

  • All students will get one (1) JITT submission that can be dropped. If for any reason you are not able to complete one of the JITTs, you can still get full credit for your submissions as long as you submit all other JITTs.

  1. Attendance/Participation (5%)
  • In order to incentivize students to show up and ask questions, attendance and in-class participation will count towards your final grade.

  • During the semester, I will record attendance for at least 5 classes (and no more than 7). Students can be absent from one of those classes, without penalty. This includes excused (through SES) and unexcused absences.

  • If a student misses more than one class where attendance is recorded, they can make up for it by participating in at least 2 classes of recorded participation. Classes where participation is recorded will be chosen randomly throughout the semester.

  • In order for in-class participation to count, students must either ask a specific question or voluntarily answer a question asked by the instructor.

  • If a student has a health issue or other extraordinary circumstances that prevent them from attending class consistently, please reach out to the instructor as soon as possible.

  1. Midterm Exam (25%)
  • The midterm exam will be an individual evaluation, in-person, during regular class time. Students will be able to use any offline resource (e.g. notes from class, slides, R scripts provided), but no online resources.

  • Just as with homework assignments, students will have to submit their R script in addition to their midterm in order to be evaluated.

  1. Final Exam (25%)
  • The final exam will be an individual in-person evaluation, and it will be cumulative. Students will be able to use some offline resources (one cheat-sheet, and one R script provided for everyone), but no online resources.

  • Just as with homework assignments, students will have to submit their R script in addition to their final exam in order to be evaluated.

Students should always reference any outside resources that they use for completing any assignment. Any unattributed content will be considered plagiarism, resulting in a failing grade and disciplinary measures.

© Magdalena Bennett - licensed under Creative Commons.