ECTS credits ECTS credits: 9
ECTS Hours Rules/Memories Student's work ECTS: 148.5 Hours of tutorials: 4.5 Expository Class: 36 Interactive Classroom: 36 Total: 225
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Statistics, Mathematical Analysis and Optimisation
Areas: Statistics and Operations Research
Center Faculty of Labour Relations
Call:
Teaching: Sin docencia (Extinguida)
Enrolment: No Matriculable
To acquire the managing, under a practical approach, of the different techniques that allow a correct and rigorous approach, collection, analysis and interpretation of information, in an investigation of the social reality and especially in a social research linked to labour relations and human resources.
The basic character of the subject makes its contents relevant to others subjects in the degree, especially for Human Resource Management, Design of Labor Processes and Labor Economics.
1. Introduction to the techniques of social research: elements and basic operations of a social research.
The scientific method and the social research. Types of social investigations. Examples of social researches. Basic elements and phases of a social research. Statistics and social Investigation
2. Techniques of data obtaining.
The observation. Questionnaires. The interview. The documentary sources.
3. Descriptive statistics.
Variable statistics. Qualitative and quantitative variables. Discrete and continuous variables. Frequency tables. Graphic representations. Central trend measurement. Form and dispersion measurement.
4. Social indicators and socio-labour statistics.
Simple indexes. Complex indexes. Deflation. Other social indicators.
5. Descriptive analysis of dependency.
Tables of contingency. Measures of association. Linear regression. Coefficient of determination.
6. Probability and maths models to the social investigation.
Outcomes of a random experiment and its probability. Variables associated to random experiments. Significant distributions.
7. Sampling as a technique of social investigation.
Different sampling methods. Sampling errors. Size of a sampling necessary to estimate an average or a proportion.
8. Tests of decision in the social investigation.
Point estimation for means and proportions. Obtaining intervals of confidence. Hypothesis tests. Level of significance.
Labs (mandatory):
Introduction to SPSS. Data analysis.
Regression and dependency of variables.
Intervals of confidence. Hypothesis tests.
The most suitable textbook for the course is:
• Fernández Sotelo, M. A.; Coladas Uría, L. (2024). Técnicas de Investigación Social. USC.
The following textbooks are recommended:
Basic bibliography:
• Alcalá, A. (1999). Estadística para Relaciones Laborales. Hespérides.
• Montero Lorenzo, J. M. (2000). Estadística para Relaciones Laborales. Editorial AC.
• Peña, D. y Romo, J. (1997). Introducción a la Estadística para las Ciencias Sociales. McGrawHill.
• Sierra Bravo, R. (1995). C. Técnicas de Investigación Social Teoría y Ejercicios. Paraninfo.
• Visauta Vinacua, B. (1997). Técnicas de Investigación Social. P.P.U.
Complementary bibliography:
• Corbetta, P. (2003). Metodología y técnicas de investigación social. McGrawHill.
• Duverger, M. (1996). Métodos de las Ciencias Sociales. Ariel.
• García Ferrando, M., Ibañes, J. Y Alvira, F. (1996). El Análisis de la Realidad Social. Métodos y Técnicas de Investigación. Alianza.
• Visauta Vinacua, B. (2007). Análisis Estadístico con SPSS 14: Estadística Básica. 3ª Edición. McGrawHill.
BASIC AND GENERAL
CG1 - Learn autonomously.
CG2 - Locate, analyze, synthesize and manage different sources and types of information.
CG6 - Work individually and in teams.
SPECIFIC
CE3 - Locate, interpret, synthesize and represent labour and socioeconomic data and indicators.
• The subject consists of nine annual credits, distributed in 45 hours of explanatory teaching and 27 hours of small groups, including the computer labs (mandatory).
• The classes will be developed in the assigned classroom using basically the blackboard and presentations. It will be promoted the participation of students at classes, especially the most practical aspects. In addition it will be discussed and solved some exercises announced in bulletins that will be delivered to the student to boost their personal work, using it to assess the better use of students too.
• Students will rely on the support of the virtual campus of the USC, through the page of the course, to have access to the programs, bibliography and different bulletins of exercises, as well as notes of some units and information about complementary voluntary activities and tools of communication.
• There will be a theoretical-practical final exam consisting of the interpretation of a series of questions, the development of theory questions and problem solving. In agreement with the students, a voluntary partial exam may be carried out, which will release the subject, at the end of the first semester. Once the final exam is passed, the grade or, in the case of passing the partial exam, the average of the two exams, will have a weight of 70% in the final grade of the subject.
• The continuous evaluation will be carried out through written controls, work delivered, attendance, participation and use of classes, tutorials and practices. This evaluation will represent 30% of the final grade.
• A fruitful attendance to computer labs will be mandatory to pass the course.
• Students with attendance waiver must take the exam or exams on-site and send interactive activities in electronic support for evaluation.
• In the case of fraudulent exercises or tests, the provisions of the "Regulations on the Evaluation of Students' Academic Performance and on the Review of Qualifications" shall apply.
• Individual study or in groups: 90 hours
• To solve practical cases or other works: 25 hours
• Recommended readings: 15 hours
• Preparation of oral presentations, debates and similar: 5 hours
The time of study necessary to pass the subject depends a lot on previous knowledge and on students’ skills. Normally, an hour of study and workload per day that complements the attendance to classes should be enough.
To pass successfully the subject it is necessary the attendance to theoretical and practical classes, and the accomplishment and review of the practical bulletins delivered at class or throughout the course.
Furthermore, in the programme there is a list of recommended tests for the subject so as to be possible to complement or extend any topic.
Maria Angeles Fernandez Sotelo
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- Phone
- 881813210
- mangeles.fernandez.sotelo [at] usc.es
- Category
- Professor: University Lecturer
Maria Jose Ginzo Villamayor
Coordinador/a- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- mariajose.ginzo [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
Angel Manuel Gonzalez Rueda
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- angelmanuel.gonzalez.rueda [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
| Thursday | |||
|---|---|---|---|
| 10:30-12:00 | Grupo A - horario de mañana (M-Z) | Spanish, Galician | Classroom 5 |
| 16:30-18:00 | Grupo B - horario de tarde (A-L) | Galician | Classroom 5 |
| 06.04.2025 09:30-12:30 | Grupo A - horario de mañana (M-Z) | Classroom 3 |
| 06.04.2025 09:30-12:30 | Grupo B - horario de tarde (A-L) | Classroom 3 |
| 06.04.2025 09:30-12:30 | Grupo A - horario de mañana (M-Z) | Classroom 5 |
| 06.04.2025 09:30-12:30 | Grupo B - horario de tarde (A-L) | Classroom 5 |
| 06.04.2025 09:30-12:30 | Grupo A - horario de mañana (M-Z) | Classroom 6 |
| 06.04.2025 09:30-12:30 | Grupo B - horario de tarde (A-L) | Classroom 6 |
| 06.23.2025 16:30-19:30 | Grupo A - horario de mañana (M-Z) | Classroom 3 |
| 06.23.2025 16:30-19:30 | Grupo B - horario de tarde (A-L) | Classroom 3 |
| 06.23.2025 16:30-19:30 | Grupo A - horario de mañana (M-Z) | Classroom 5 |
| 06.23.2025 16:30-19:30 | Grupo B - horario de tarde (A-L) | Classroom 5 |
| 06.23.2025 16:30-19:30 | Grupo A - horario de mañana (M-Z) | Classroom 6 |
| 06.23.2025 16:30-19:30 | Grupo B - horario de tarde (A-L) | Classroom 6 |