Teachers: Eugenio Cinquemani (, Vittorio Perduca (TA)

Schedule: 11 sessions of 3 hours each (2 hours teaching and 1 hour practice per session) + open discussion sessions to be determined with students


Overview of the class:

After an introductory discussion of the rationale of a probabilistic framework, we will briefly review the fundamental concepts of probability theory, and then develop and discuss commonly used methods for estimation and hypothesis testing (comparison of means, correlation analysis, regression, analysis of variance with parametric and non-parametric approaches). We will rely on rigorous but simple mathematical developments, putting emphasis on conceptual issues. In pace with the teaching sessions, in  the practical sessions we will apply the tools discussed to example problems including real-world data. Possibility of extra-modules on advanced topics.


Course objectives:

The course aims at developing the students’ critical thinking and ability to formalize a scientific question in a probabilistic framework. While providing a broad coverage of practical tools for statistical analysis, the objective is to bring students to a level of autonomy in seeking the right tools for the problems they will encounter in their career.



Elements of calculus and descriptive statistics, basic knowledge of R (all covered in the bootcamp)