Course overview

This is the homepage for MATH-516 Applied Statistics in Spring 2025 at EPFL. All course materials will be posted on this site.

You can find the course syllabus here and the course schedule here. All the additional ressources can be found either on this page or by using the search bar on the top left corner of the website. These ressources include project descriptions, datasets, tips and tricks, etc…

1 Course Organization

Meeting Location Time
Lectures MA A3 31 Mon 13:15 - 14:00
Exercises MA A3 31 Mon 14:15 - 17:00

2 Course Content

Apart from the topics mentioned in the schedule, mastering this course requires scripting (simulation studies and data exploration & visualization tasks), as well as sharing your code via GitHub. Check out this manual from the previous course (MATH-517, a mandatory prerequisite). Exercise classes should be attended and used to pick up the required skills, and work on the projects!

3 Evaluation

The assessment method for this course is “controle continue”, meaning that the course and all the work required from the students effectively end with the end of the semester.

Project 1 is mandatory (deadline in Sunday, March 2) and the course is “without withdrawal”, i.e., whoever submits Project 1 is committing to the course and will eventually get a grade.

There will be 7 projects (data analyses) in total:

  1. Fundamental frequency of vowels
    • Weeks 1 and 2 (17.2.-2.3.2025)
  2. GLMs - TBD
    • Weeks 3 and 4 (3.3.-16.3.2015)
  3. Causal Discovery - TBD
    • Weeks 5 and 6 (17.3.-30.3.2025)
  4. Linear Mixed Models - TBD
    • Weeks 7 and 8 (31.3.-.13.4.2025)
  5. Extreme Value Theory - TBD
    • Weeks 9 and 10 (14.4.-4.5.2025)
  6. Statistical Consulting - TBD
    • Weeks 11 and 12 (5.5.-18.5.2025)
  7. Oral Exams
    • Week 13 and 14 (19.5.-30.5.2024)

Of these 6 projects, every student needs to work 4 of them. Three projects are mandatory and one can be chosen from a subset of projects:

- Project 1 is mandatory,
- Project 3 is mandatory,
- Project 5 is mandatory,
- Projects 2,4,6: choose one of them.

The projects will be worked out and handed in by each student individually, but collaborations in small groups is encouraged as long as other students’ work and ideas are attributed properly in each idividual project.

Grading

Deadlines will always be set at the end of the week (23:59 on Sunday). A project from Week \(k\) (given on Monday) will always have its deadline on Week \(k+1\) (i.e., the midnight between Sunday and Monday following the \((k+1)\)-th week, see the schedule).

4 Materials

All materials will be gradually made available on this website. Lectures and Projects can be accessed through their respective tabs. Lecture slides as well as projects’ descriptions will be posted in the schedule.

5 Handing-in Projects

We will use GitHub Classroom to handle the projects for this course. See this page for more information on how to use GitHub Classroom.


5.1 License

Creative Commons License
This online work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International. Visit here for more information about the license.

This website and part of the course materials were adapted from different sources: