Probability and statistics

The goal of the course is to provide notions of descriptive statistics, probability theory and statistical inference that constitute the foundation of applied research in economics. The aim is to develop the proper technical language and to enable students to attend more specialized courses such as "Econometrics" and "Machine Learning for Economics".

At the end of the course, the student will have acquired the main tools related to descriptive statistics (construction of indices, tables and graphs and interpretation of the same), probability theory (Bayes theorem, probability distribution and random variables) and statistical inference (point estimation, confidence intervals and hypothesis testing).
Students will be able to apply the studied statistical techniques to analyse data and solve common real-life problems. They will be able to interpret the most common statistical indices; calculate and interpret point estimates, and confidence intervals and test the most common statistical hypothesis, such as equality of means and independence between variables. Moreover, they will be able to perform a simple linear regression and interpret the output through statistical software.