Formation/Cours

This course aims to introduce students to the statistical concepts and methods essential for understanding empirical research in political science. By the end of the course, students should have a solid grasp of the research process, including the formulation of theories and hypotheses, and the classification of variables. They should understand the main tools of descriptive statistics, probability theory, and statistical inference, and be able to interpret statistical relationships and evaluate empirical evidence.

Through guided exercises and applied examples, students will also become familiar with the structure of social science datasets and acquire basic skills in reading, interpreting, and reporting statistical outputs. They should be able to understand univariate and bivariate statistical analyses, interpret the results of common statistical procedures, and critically assess their relevance for political science research.

This course offers a theoretical introduction to the statistical concepts underpinning empirical research in political science. It begins with the research process, hypothesis formulation, and the classification of variables. It then examines the fundamentals of descriptive statistics, including frequency distributions, data visualisation principles, and measures of central tendency and dispersion. The course proceeds with probability theory, the normal distribution, sampling distributions, and the core logic of statistical inference, namely confidence intervals, hypothesis testing, and errors of inference. Finally, it addresses group comparisons, associations between categorical variables, and the principles of correlation and regression analysis.