PhD programmes - Humanities
Doctoral programme
International Studies
Home > Programme > PhD Courses > Game theory and network analysis
Home > Programme > PhD Courses > Game theory and network analysis

Game theory and inferential statistics

Quantitative methods

Acquire a basic knowledge of model formulation, using game theory, and parameter estimation, using statistical inference. At the end of the course, students should be able to recognize the main underlying process (e.g. the structure of the game) of political, economic and social interactions. Students should also develop skills of data analysis using appropriate software and gaining the ability to interpret results in scientific publications. 

Course Description
The course is divided essentially into two parts. The first introduces students to game theory, as a formal model to describe and forecast the outcome of social interaction. The second part of the course aims to provide the basic elements of probability and statistical inference. Throughout the course, Excel (or analogous software) will be used both to perform statistical analysis on real data sets and to perform simulated probabilistic experiments (via the Monte Carlo method).

Major Teaching Topics:

  • Game Theory and Statistics for Political Sciences
  • Games in normal form and extensive form. Solution concepts: Backward induction, Nash Equilibria.
  • Some classic games in International Affairs: zero-sum, chicken (hawk and doves), battles of the sexes, prisoner’s dilemma.
  • Mixed strategy equilibria and the evolution of norms.
  • Statistics Inference on Political Data: Inference on probabilities, expectations and variances; Bivariate analysis on categorical variables: two-way tables;
  • Bivariate analysis of numerical variables: linear regression.


The exam consists of the exposition of selected papers by students. Full lists will be available during the course and depend on student’s research projects.

For the courses schedule please refer to the Calendar