Degree | Type | Year | Semester |
---|---|---|---|
2500259 Political Science and Public Management | OB | 3 | 1 |
Students should have acquired basic concepts of research methods. It is highly advisable that they have completed the compulsory course of Methodology of Political Analysis. They must be able read English and work with spreadsheets (Excel).
The aim of this course is that students familiarize with the main social science research techniques and learn how to use them. The bulk of the course is devoted to linear regression analysis and its extensions. We will prioritize practical training and the interpretation and presentation of results over mathematical issues. At the same time, the course will introduce students to the R language of statistical computing through RStudio, to provide the essential skills for data management, exploratory data analysis, data visualization, reproducibility, and effective communication of results. Throughout the course we will work with real-world, socially- and politically-relevant data, while also encouraging a critical and responsible usage of open data.
1. Data visualization and exploratory data analysis
2. Data management
3. Simple linear regression
4. Multiple regression
5. Categorical independent variables
6. Regression models for categorical dependent variables
There are two types of directed activities:
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Lab and in-class exercises | 19.5 | 0.78 | 1, 5, 4, 6, 7, 11, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
Lectures | 30 | 1.2 | 1, 5, 4, 6, 7, 11, 9, 12, 13, 17, 10, 15, 14, 3, 2 |
Type: Supervised | |||
Tutorials | 15 | 0.6 | 1, 5, 4, 6, 7, 11, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
Type: Autonomous | |||
Study | 83.5 | 3.34 | 1, 5, 4, 6, 7, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
The evaluation will be based on the following activities:
To pass the course, it is required that all of the following conditions are met:
Retake process
Only the exam is recoverable; in-class exercises and lab assignments are excluded from the retake process.
To be eligible to participate in the retake process, it is required that both these conditions are met:
Important considerations
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Final exam | 50% | 2 | 0.08 | 1, 5, 4, 6, 7, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
In-class exercises | 10% | 0 | 0 | 1, 5, 4, 6, 7, 11, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
Lab assignments | 40% | 0 | 0 | 1, 5, 4, 6, 7, 11, 9, 8, 12, 13, 17, 16, 10, 15, 14, 3, 2 |
Basic
Complementary