| Jean Clipperton | |
|---|---|
| clipperton@uchicago.edu | |
| Office | Room 219, 1155 E. 60th St. |
| GitHub | jmclip |
- Meeting day: August 25-September 12, MTWThF
- Time: 9:00am-1:00pm
- Location: Social Sciences Rsch Bldg 122
- Bailey Meche baileymeche@uchicago.edu
- Gabe Reichman gabereichman@uchicago.edu
- Shirley Zhang xueyan1220@uchicago.edu
- Stanley Yi yijiaying@uchicago.edu
| In-person | Zoom | |
|---|---|---|
| Monday | ||
| Tuesday | 12-1 PM (Stanley), 5-7 PM (Gabe) | 7-8 PM (Stanley) |
| Wednesday | 12-1 PM (Shirley & Stanley) | 8-10 PM (Shirley) |
| Thursday | 12-1 PM(Shirley), 5-7 PM (Gabe-9/11 only) | 7-8 PM (Stanley) |
| Friday | 4-6 PM (Gabe) | |
| Saturday | 9 AM - 12 PM (Bailey) |
This course surveys mathematical and statistical tools that are foundational to computational social science. Topics to be reviewed include mathematical notation and linear equations, calculus, linear algebra, probability theory, and statistical inference. Students are assumed to have encountered most of these topics previously, so that the camp serves as a refresher rather than teaching entirely new topics. Class sessions will emphasize problem solving and in-class exercises applying these techniques. Students who successfully complete the camp are situated to pass the MACSS math and statistics placement exam and enroll in computationally-enhanced course offerings at the University of Chicago without prior introductory coursework.
-
Students in the Masters in Computational Social Science
-
MA and PhD students in the social sciences who have significant prior training and experience in mathematics and statistics and seek to complete the Certificate in Computational Social Science
-
Students looking for a slower-paced camp focused specifically on algebra, calculus, and probability should enroll in SOSC 30100 - Mathematics for Social Sciences. This two-week course makes no assumption of prior math/stats training. Those of you who struggle with the material of this course may switch after the first week to SOSC 30100.
Attendance is expected but not required. Students are responsible for the content covered in class.
Students can withdraw at any point in the course without penalty. Only students who pass the course have it on their transcript (no W will appear).
Join our canvas classroom by clicking this link This code should enable anyone to join. For assignments, please be sure to upload a CLEAR AND READABLE DOCUMENT that is labeled with the assignment name and your name.
This course may only be taken for pass/fail (non-credit), not for a letter grade or audit. Assignments are comprised of daily problem sets. You are encouraged to work in groups, and the instructional staff is available for consultation during class hours. We expect most students should be able to finish the problem sets during class hours. Grades will be based upon performance on the problem sets and in the final exam.
We have regrading open on Gradescope. You should request a regrade if there is an error in the grading (e.g. something was marked as incorrect but it was actually correct). Regrades are open for approximately one week or 9/16, whichever is sooner. Note that there are required portions that must be tagged (e.g. name and AI/resources statement). Failure to tag them (even if they are there) after PSET 2 will result in a forfeit of those points.
The regrade space is pretty limited -- you need to be clear, professional, and direct. Note that tone can come across very differently in writing versus in person so please be mindful. I (Jean) will step in as needed if you have questions.
The final exam is in-person, on paper only. You may bring one double sided sheet of notes (regular 8.5 x 11") and a non-graphing calculator. The study sheets will be collected at the end of the exam. One example kind of calculator would be this calculator. Loaner calculators (total of about 11) are available by request if requested by 9/9/25. Exam questions + Calc request
For course credit, students need to complete at least six assignments at or above 70% and get a 70% or higher on the final exam. If students complete six assignments at or above 70% but score between 50% and 70% on the final exam, the students can complete one additional exam for course credit. Note that if MACSS students do not meet the requirements for passing on the first assessment, they can still earn credit for the course but will still need to take a supplemental methods course per our program policy.
Attendance is not required with the exception of the final day of class, which has the final exam. The exam is not optional and is in-person only.
AI / generative AI / GPT-like tools are not permitted for any of the assessments in this course. You may use it to understand logic of non-assignment questions / sample questions. Each assignment requires a statement of the resources you used in the assigment.
Using these tools constitutes academic dishonesty and will be reported to the Dean of Students, Kelly Pollock. Academic integrity is something we take very seriously: violations are not tolerated.
Submit your practice questions here. We will use this to generate the final exam and we will circulate the questions here to all students. Note that not all questions here will be on the exam -- it depends upon the quality and variety of submissions.
The University of Chicago is committed to diversity and rigorous inquiry from multiple perspectives. The MAPSS, CIR, and Computation programs share this commitment and seek to foster productive learning environments based upon inclusion, open communication, and mutual respect for a diverse range of identities, experiences, and positions.
This course is open to all students who meet the academic requirements for participation. Any student who has a documented need for accommodation should contact Student Disability Services (773-702-6000 or disabilities@uchicago.edu) as soon as possible.
Course texts are subject to change for 2025
- Bertsekas, D. P., & Tsitsiklis, J. N. (2008). Introduction to probability, 2nd edition. Belmont, MA: Athena Scientific.
- Pemberton, M., & Rau, N. (2015). Mathematics for economists: an introductory textbook, 4th edition. Oxford University Press.
Note: solutions posted after grades released