Degree | Type | Year | Semester |
---|---|---|---|
2500259 Political Science and Public Management | OB | 2 | A |
2503778 International Relations | OB | 2 | A |
No necessary prerequesite required.
The course aims to be an introduction to the different stages in political science and international relations research. The fundamental purpose of the course is to provide the student with the resources that will enable them to be able to produce knowledge through original research and critically evaluate the work from other authors. The course covers all the aspects necessary to understand the logic of political research: the different ways of producing knowledge, the formulation of questions and hypotheses, the treatment of concepts and the collection and analysis of data.
The main objectives of the course are:
1. The research question
The research question: what? who? how? why?
The tentative answers: the review of the literature and the elaboration of the theoretical framework
The hypotheses
2. Use and measurement of concepts
The organization of the data: units, variables and observations, and data set dimensions
From concepts to variables: the process of operationalization
Independent variables and dependent variables
Measurement levels and type of variables
Measurement error: validity and reliability
3. Univariate descriptive analysis
The statistical description
Measures of centrality
Measures of dispersion
Graphic representations
4. Control of alternative explanations and research design
What should an explanation contain?
Causality: the relationship between variables
Control methods: experimental and observational studies (statistical and comparative methods, case studies)
Longitudinal and cross-sectional designs
5. Data collection
Data sources for political analysis
The standardized interview: the questionnaire
The qualitative interview: structured, semi-structured and unstructured interviews
Other ways to generate data: participant observation, document analysis
6. Random sampling and inference
Population and sample
Representativeness and generalizability
Types of random sampling
The normal distribution and the sampling distribution
Sampling error and confidence level
Sample size
Statistical inference
Significance level
7. Bivariate relationships (1) Tabular analysis
Relationships between variables and hypothesis testing
Tabular analysis: cells, columns and rows
Types of tables: row, column and total percentages
How to interpret the tables?
Measures of the degree of association between variables
Statistical hypothesis test: the chi-squared test (χ2)
8. Bivariate relationships (2) Correlation and difference of means
Difference of means
Statistical hypothesis test: Student's t-test
Scatterplots
Correlation and Pearson’s R
9. Bivariate relationships (3) Regression model
Simple linear regression
Regression line
Regression coefficients
The constant
R-squared statistic
To achieve the objectives of the course, the teaching plan includes two types of sessions: theory sessions and practical sessions.
The sessions will be oriented to the assimilation of the subject contents, which will have to be demonstrated in the different assessment tests.
The work sessions of the students will be devoted to elaborate exercises that require the use of the techniques data collection and analysis covered during the course.
Students will get familiarised with the usage of Excel and Jamovi software. They will use this software to conduct the different analyses that they will be required carry out throughout the academic year.
As a pilot test, group 52 (International Relations degree) will be organised with another lessons order.
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 | |||
Exercises presentation | 15 | 0.6 | 2, 9, 10, 13, 11, 15, 19, 5, 7 |
Practical lessons with computer | 30 | 1.2 | 2, 9, 11, 15, 19, 12, 18, 17, 5 |
Theoretical lessons | 60 | 2.4 | 2, 9, 10, 12, 5, 4 |
Type: Supervised | |||
Tutorials to support exercises elaboration | 30 | 1.2 | 9, 10, 12, 5, 4 |
Type: Autonomous | |||
Exercices | 60 | 2.4 | 2, 9, 8, 10, 16, 11, 3, 14, 15, 19, 12, 18, 17, 5, 6, 4 |
Readings | 30 | 1.2 | 2, 9, 11, 15, 19, 18, 4, 7 |
Study | 60 | 2.4 | 2, 11, 3, 15, 19, 12, 17, 5, 4 |
1. Exam on January (35 % of the final grade), on the date set by the faculty.
2. Exam on June (35% de la nota final), on the date set by the faculty.
3. Practical examination (30% of the final grade). Within the section of the practical examination it is included:
- Individual tests aimed at checking the achievement of knowledge. Some of them will be computer-based.
There will be a total of 6 individual tests along the course. (30% of the final mark).
Important considerations:
COMPENSATION TESTS
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Final exams | 70% | 3 | 0.12 | 9, 11, 15, 19, 18 |
Practical examination | 30% | 12 | 0.48 | 1, 2, 9, 8, 10, 16, 13, 11, 3, 14, 19, 12, 18, 17, 5, 6, 4, 7 |
Manual reference
Corbetta, Piergiorgio. 2003. Metodología y técnicas de investigación social. Madrid: McGraw-Hill
Further readings
Crespo, Ismael; Anduiza, Eva, & Méndez, Mónica. 2009. Metodología de la ciencia política. Madrid: Centro de Investigaciones Sociológicas.
Manheim, Jarol B. & Richard C. Reich. 1986. Análisis político empírico. Métodos de investigación en ciencia política. Madrid: Alianza.
Morales Vallejo, Pedro. 2008. Estadística aplicada a las Ciencias Sociales. Madrid: Universidad Pontificia Comillas.
Ritchey, Ferris Joseph. 2002. Estadística para las ciencias sociales: el potencial de la imaginación estadística. México: McGraw-Hill.
Cea, M. Ángeles. 2004. Métodos de encuesta. Teoría y práctica, errores y mejora. Síntesis: Madrid.
Excel and Jamovi