The main objective of this course is to familiarize students with statistical inference techniques (estimation, confidence intervals, hypothesis tests, and regression models) and to be able to correctly interpret statistical results.
The second objective is more practical. Students will have to be able to analyze and solve a data analysis problem using quantitative tools (including the use of computer software), as well as to interpret the obtained results.
The main objective of this course is to familiarize students with statistical inference techniques (estimation, confidence intervals, hypothesis tests, and regression models) and to be able to correctly interpret statistical results.
The second objective is more practical. Students will have to be able to analyze and solve a data analysis problem using quantitative tools (including the use of computer software), as well as to interpret the obtained results.
After a brief introduction to the concepts of parameter, estimator and statistical inference, the course gives an introduction to simple and multiple linear regression models. Multicollinearity and specification issues are discussed. Special attention is given to binary variables.
The exam will be written in one part, with questions that may cover:
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Bachelor in Information and Communication | Standard | 0 | 5 | |
| Bachelor in Political Sciences : General | Standard | 0 | 5 | |
| Bachelor in Political Sciences : General | Standard | 2 | 5 | |
| Bachelor in Information and Communication | Standard | 2 | 5 |