ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Hours of tutorials: 3 Expository Class: 24 Interactive Classroom: 24 Total: 51
Use languages Spanish (7%), Galician (92%)
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Quantitative Economy
Areas: Quantitative Economics (USC-specific)
Center Faculty of Communication Science
Call: First Semester
Teaching: Sin docencia (Extinguida)
Enrolment: No Matriculable
The course introduces students to the basic statistical knowledge and techniques for the preparation of numerical and qualitative reports and summaries. It analyses the treatment of statistical information in the media, the main statistical operations applied to communication, the potential of statistics in the handling of big data through applications, and the interpretation of results.
Summary and dissemination of statistical information. Analysis and descriptive summary of data, relationships between variables, samples, time series data, index numbers, variations. Statistical methods applied in the preparation of information and research in communication. Statistical computer support. Databases in the field of communication and their analysis.
THEORETICAL CONTENT
UNIT 1. INTRODUCTION
1.1 Introduction to Statistics
1.2 General Concepts of Statistics
UNIT 2. ANALYSIS OF ONE VARIABLE
2.1 Tabulation of variables and frequency distributions
2.2 Graphical representations
2.3 Measures of central tendency
2.4 Measures of dispersion
2.5 Measures of shape
UNIT 3. ANALYSIS OF MORE THAN ONE VARIABLE. RELATIONSHIPS
3.1 Bivariatel distributions. Tabulation
3.2 Graphical representations.
3.3 Relationships between variables. Independence
3.4 Correlation and association.
UNIT 4. INDEX NUMBERS
4.1 Key rates of variation.
4.2 Simple and composite indexes
4.3 Base change
4.4 Prices, quantity, and value indices
4.5 Deflation
4.6 Consumer price index. Other indicators
UNIT 5. TIME SERIES
5.1. Descriptive modelling of a time series
5.2. Components of a time series
UNIT 6. SAMPLING AND DATA IN COMMUNICATION
6.1 Introduction to sampling
6.2 Main sampling techniques
6.3 Applications. Major surveys.
UNIT 7. STATISTICS AND INFORMATION TECHNOLOGY
7.1 Statistical software packages and applications.
7.2 Sources of statistical information on the web (IGE, INE, Eurostat, MC Yearbook,...)
PRACTICAL CONTENT
Practical activities will be carried out (exercise solving, computer software usage, etc.) related to all theoretical content topics.
BASIC BIBLIOGRAPHY
Jauset, J. (2007). Estadística para periodistas, publicitarios y comunicadores : aplicaciones de los porcentajes y diseño e interpretación de encuestas : 110 ejercicios y cuestiones prácticas. UOC.
Peña, D. & Romo, J. (2003). Introducción a a la estadística para las ciencias sociales. McGraw Hill.
Pérez, C. (2002). Estadística aplicada a través de Excel. Pearson Educación.
Portilla, I. (2004). Estadística descriptiva para comunicadores: aplicaciones a la publicidad y las relaciones públicas. EUNSA.
COMPLEMENTARY BIBLIOGRAPHY
Busquet Durán, J. & Medina Cambróns, A. (2017). La investigación en comunicación: ¿que debemos saber? ¿que pasos debemos seguir? Editorial UOC. https://elibro-net.ezbusc.usc.gal/es/lc/busc/titulos/59094
Fernández Cuesta, C. & Fuentes García, F. (1995). Curso de Estadística Descriptiva. Teoría y práctica. Ariel.
Gonick, L. & Smith, G. (2001). A estatística !en caricaturas!. SGPEIO.
Humanes, M.L. (2015). Métodos de investigación en comunicación: ejercicios aplicados a las técnicas cuantitativas. Ommpress.
Jauset, J. (2000). La investigación de audiencias en televisión. Fundamentos estadísticos. Paidós.
Pulido San Román, A. (1984). Estadística y técnicas de Investigación Social. Pirámide S.A.
Sierra, R. (1994). Técnicas de investigación social. Paraninfo.
Tanur, J.M. (1992). La Estadística: Una guía a lo desconocido. Alianza Editorial.
Wimmer, R. & Dominick, J. (1996). La Investigación científica de los medios de comunicación : una introducción a sus métodos. Bosch.
Wimmer, R.& Dominick, J. (2001). Introducción a la investigación en medios masivos de comunicación. International Thomson Editores.
BASIC AND GENERAL COMPETENCES
GC1 - Acquire and understand the most important concepts, methods, and results of the different branches of communication, with a historical perspective on their development.
GC2 - Gather and interpret relevant data, information, and results and drawing conclusions and issue reasoned reports.
GC3 - Apply acquired theoretical and practical knowledge, as well as analytical and abstract thinking skills, in defining and addressing problems and finding solutions in academic and professional contexts.
CB2 - Aply knowledge to their work or vocation in a professional way, demonstrating competencies through argumentation and problem-solving within their fields of study.
CB3 - Gather and interpret relevant data (usually within their field of study) to make judgments that involve reflection on social, scientific, or ethical issues.
CB4 - Communicate information, ideas, problems, and solutions to both specialized and non-specialized audiences.
CB5 - Develop the necessary learning skills to pursue further studies with a high degree of autonomy.
with a high degree of autonomy
TRANSVERSAL COMPETENCES
CT01 - Capacity for organization and planning
CT02 - Information management skills
CT03 - Teamwork skills
CT04 - Autonomous learning
CT05 - Creativity
CT06 - Initiative and entrepreneurial spirit
CT07 - Basic knowledge of the profession
SPECIFIC COMPETENCES
CE09 - Prepare for the management of companies related to the audiovisual sector.
CE10 - Acquire the necessary techniques for the professional development of audiovisual product programming.
CE07 - Develop professional competences for distribution and exhibition of audiovisual works.
CE08 - Acquire the necessary training for interpreting statistical reports.
The course consists of a total of 6 ECTs, half of which are dedicated to lecture-based classes, and the remaining to interactive classes. The courese will not have two completely separate parts of theory and practice; both will be developed together throughout the course. The teaching materials will be provided on the Virtual Course of the subject, and their use will also be considered in the teaching methodology.
Lecture-based classes will be used for in-person activities that do not require active student participation and where the number of students per group is not a critical factor for their development: content-presentation and debates.
Interactive classes will be organized for in-person activities that seek or require active student participation: discussion of practical cases, problem-solving, working with texts or data, computer-based exercices, and presentation of assigments.
Tutorials are intended for in-person activities focused on guidance, facilitation and tutoring of student work. These sessions will provide guidance for completing assigments, preparing presentations, searching and selecting bibliographic material and statistical sources, as well as reviewing exercices or problems.
The final individual exam will be conducted in person on the dates established by the Faculty. The continuous assessment of students will be based on assigments and/or surveys carried out or assigned throughout the course, group work, and participation in academic activities. The different assessable activities throughout the course will be presented in face-to-face sessions and documented in the virtual classroom.
1st OPPORTUNITY
-Final exam: 50% of the total grade.
-Continuous assessment activities: 50% of the total grade. The evaluation system will be based on the active class attendance, student practices during and outside of class hours, as well as the quality of the assignments completed throughout the course.
To pass the course, it will be mandatory to obtain a minimum of 3 points out of 10 in the final exam.
2nd OPPORTUNITY
The evaluation method described for the 1st opportunity also applies to the 2nd opportunity. In this 2nd opportunity, the grade for continuous assessment activities will not be subject to recovery, and students can recover their exam grade through a final exam.
Students who are exempt from class attendance will be required to take the final exam, which will represent 100% of the grade. These conditions apply to both the 1st and 2nd opportunities.
• Requests for exemptions from class attendance must be authorized by the Academic Commission.
• In the event of plagiarism or improper use of technology in completing assignments or exams, the regulations outlined in the "Evaluation of Students' Academic Performance and Grade Review" policy will be applied.
• According to the current retention regulations at USC for undergraduate and master's students (article 5.2), attendance and active participation in interactive classes will be evaluated. As a result, students who meet these requirements will not receive a "Absent" grade.
Students will have the following scheduled training activities:
- Expository classes: Presentation and explanation of topics: 20 h
- Text work: Analysis, synthesis, and discussion: 5 h
- Seminar: 15 h
- Coursework tutoring: 2 h
- Assessment activities: 3 h
- Final exam: 3 hours
- Individual or group autonomous study: 45 h
- Recommended readings: 15 h
- Preparation of oral presentations, debates, etc.: 10 h
- Seminar planning: Research, recording, and preparation of supporting materials (texts, images, audio, etc.): 20 h
Mathematical language is necessary for the development of the course. Students need to make an effort at the beginning of the course to use precise language.
Student need to acquire the necessary tools for the accurate interpretation of statistical results obtained or collected from other sources. Classroom discussions about the contents are a useful tool for understanding the topics, so attending academic activities is important. It is advisable for students to consult any doubts they may have, considering the role that interpreting and using statistical results will paly in their future professional work.
Mathematical expressions do not need to be memorized by the students; they will be provided when needed. This apporach aims to develop the skills in the analysis and interpretation of results found in media sources.
Use of Virtual Classroom: yes
Interactive Teaching: Computer Lab, Whiteboard Classroom
Software: EXCEL, SPSS
Carlos Pio Del Oro Saez
- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- carlospio.deloro [at] usc.es
- Category
- Professor: University Lecturer
Maria Luisa Chas Amil
Coordinador/a- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- Phone
- 881811549
- marisa.chas [at] usc.es
- Category
- Professor: University Lecturer
| Monday | ||
|---|---|---|
| 10:00-11:00 | Expositivo 1 | Classroom 6 |
| Wednesday | ||
| 11:00-12:00 | Expositivo 1 | Classroom 6 |
| Friday | ||
| 11:00-12:00 | Expositivo 1 | Classroom 6 |
| 01.08.2024 16:00-20:00 | Expositivo 1 | Classroom 4 |
| 01.08.2024 16:00-20:00 | Expositivo 1 | Classroom 5 |
| 06.10.2024 10:00-14:00 | Expositivo 1 | Classroom 5 |
| Teacher | Language |
|---|---|
| ORO SAEZ, CARLOS PIO DEL | Spanish |
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |
| Teacher | Language |
|---|---|
| CHAS AMIL, MARIA LUISA | Galician |