| Study programme competencies |
| Code | Study programme competences |
| A1 | CE1 - Know and understand the theoretical and methodological principles of information and documentation management to apply them in their professional activity |
| A8 | CE8 - Master the different methods of representation of data, information and knowledge that ensure efficient recovery |
| A13 | CE13 - Know and master the techniques and regulations for the creation and authentication, meeting, selection, organization, representation, preservation, recovery, access, dissemination and exchange, and evaluation of resources and information services |
| A20 | CE20 - Master the bases to develop research activities using multidisciplinary methods and principles |
| A21 | CE21 - Possess knowledge of statistics and quantitative analysis of information |
| A22 | CE22 - Acquire computational skills and management of new ICT |
| B1 | CB1 - Possess and understand knowledge that provides a basis or opportunity to be original in the development and / or application of ideas, often in a research context |
| B2 | CB2 - Apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of study |
| B3 | CB3 - Be able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments |
| B4 | CB4 - Know how to communicate their conclusions -and the knowledge and ultimate reasons that sustain them- to specialized and non-specialized audiences in a clear and unambiguous way |
| B5 | CB5 - Possess the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous |
| B6 | CG1 - Capacity for cooperation, teamwork and collaborative learning |
| B7 | CG2 - Capacity for reflection and critical reasoning |
| B8 | CG3 - Capacity for planning, organization and management of resources, information and operations |
| B9 | CG4 - Capacity for analysis, diagnosis and decision making |
| B10 | CG5 - Ability to work in an international and global context |
| B11 | CG6 - Ability to understand the importance, value and function of the Digital Information and Documentation Management in the current ICT society |
| C1 | CT1 - Express correctly, both orally and in writing, in the official languages ??of the autonomous community |
| C2 | CT2 - Use the basic tools of information and communication technologies (ICT) necessary for the exercise of their profession and for learning throughout their lives |
| C3 | CT3 - Develop oneself for the exercise of a citizenship that respects democratic culture, human rights and the gender perspective |
| C4 | CT4 - Understand the importance of the entrepreneurial culture and know the means available to entrepreneurs |
| C5 | CT5 - Acquire skills for life and habits, routines and healthy lifestyles |
| C6 | CT6 - Develop the ability to work in interdisciplinary or transdisciplinary teams, to offer proposals that contribute to a sustainable environmental, economic, political and social development |
| C7 | CT7 - Assess the importance of research, innovation and technological development in the socio-economic and cultural progress of society |
| C8 | CT8 - Have the ability to manage time and resources: develop plans, prioritize activities, identify criticisms, establish deadlines and comply with them |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| To know the basic inference techniques and acquisition of skills for the estimation and interpretation of confidence intervals and hypothesis testing of one and two populations. | A8 A13 A21 |
B1 B8 B9 |
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| To know the main types of sampling and the basic tools for survey design. | A1 A13 A20 A21 |
B2 B3 B4 B5 B9 |
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| Ability to compare two or more populations from databases of different degrees of complexity. | A1 A21 |
B1 B2 B3 B4 B5 |
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| Knowledge of the different multivariate data analysis techniques to describe and obtain relevant information from complex databases. | A1 A20 A21 |
B1 B2 B3 B4 B5 |
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| Ability to use computational tools for multivariate data analysis. | A22 |
B11 |
C2 C6 C8 |
| Integrate theoretical and practical statistical knowledge as a way to knowledge and reflective and totalizing thinking. | A1 A13 |
B2 B3 B4 B5 B6 B7 B10 |
C4 C7 C8 |
| Capacity of analysis and synthesis applied to the management and organization of information. | B2 B3 B4 B5 B6 B7 B8 B9 |
C1 C3 C5 |
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| Acquisition of decision-making skills based on statistical analysis of complex databases. | A21 |
B2 B3 B8 B9 |
C8 |
| Contents |
| Topic | Sub-topic |
| The following topics develop the contents established in the file of the Verification Report, being: | Introduction and main statistical concepts related to sampling and survey design. Introduction to statistical inference and point estimation. Confidence intervals. Hypothesis testing. Analysis of variance (ANOVA). Regression models. Other multivariate analysis techniques. Computational tools for the generation of statistical reports. |
| 1. Sampling and surveys: introduction and main concepts. | General concepts of statistical sampling and survey design. |
| 2. Introduction to statistical inference and point estimation. | General concepts. Sampling. Parameter estimation. Properties of estimators. Point estimation: point estimation of the mean, variance and a proportion. |
| 3. Confidence intervals. | Concept of confidence interval. Confidence interval for a mean, for a variance, for a proportion and for the difference of two means. |
| 4. Hypothesis testing. | General concepts. Hypothesis testing for the mean, the proportion and for the difference of two means. Independence contrasts. |
| 5. Analysis of variance (ANOVA). |
Graphical ANOVA. ANOVA of one factor. ANOVA of more than one factor. |
| 6. Regression models. |
Simple and multiple linear regression model. Other regression models. |
| 7. Other multivariate analysis techniques: principal component analysis, factor analysis, correspondence analysis, multidimensional scaling. | Introduction to the most used multivariate techniques. |
| 8. Computational tools for the generation of statistical reports. | Introduction to different tools of the statistical software R for the generation of reports: Rstudio, Rmarkdown, Graphics with R, Htmlwidgets. |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A1 A8 A20 A21 B1 B3 B7 C4 C7 | 21 | 0 | 21 |
| ICT practicals | A13 A22 B11 C2 | 12 | 0 | 12 |
| Case study | A1 A8 A21 B2 B3 B4 B5 B6 B7 B8 B9 C1 C8 | 7 | 7 | 14 |
| Supervised projects | B2 B4 B5 B6 B8 B9 B10 C1 C3 C5 C6 C8 | 1.02 | 100.98 | 102 |
| Objective test | A21 B1 B2 | 1 | 0 | 1 |
| Personalized attention | 0 | 0 | 0 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Guest lecture / keynote speech | Keynote speech will be given in which the teacher will explain, with the help of appropriate audiovisual media, the main contents of the subject. |
| ICT practicals | In the practical classes the student will be introduced to the handling of the statistical software R. Computational tools for the resolution of problems will be shown and applied through the statistical analysis of data, either from simulated or real data. |
| Case study | The statistical techniques taught in the course will be applied to solve exercises and real and simulated case studies in the field of digital information management. |
| Supervised projects | Students will be proposed to develop a group work (2 to 4 people) consisting of the application of statistical and computational tools shown in class to a particular case study, described by real or simulated data. You can also perform a work consisting of the description of a case study in the field of communications and information sciences, in which the resolution of a real problem is carried out based on the application of statistical techniques. A review study on a specific topic of the subject or the software used may also be carried out. The works can be proposed by the teachers or by the students themselves (the proposals will be taken into account or not always according to the teacher's criteria). |
| Objective test | It will consist of a multiple-choice test on the contents taught in the course. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| ICT practicals | A13 A22 B11 C2 | The attendance and performance of the student in the practical classes will be evaluated, as well as the delivery of works related to the application of the statistical software R. | 20 |
| Objective test | A21 B1 B2 | It will consist of 15 to 20 test questions with three possible answers. | 40 |
| Supervised projects | B2 B4 B5 B6 B8 B9 B10 C1 C3 C5 C6 C8 | These works will be carried out in groups of 2 to 5 people, applying statistics to real or simulated data, reviewing a topic on statistics or data science or even regarding a specific application of statistics related to the field of communication and information scienses. | 40 |
| Assessment comments | |||
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First chance evaluation There will be a multiple-choice objective test of 10 to 20 questions that represents 40% of the grade. On the other hand, the continuous assessment will consist of attendance and / or delivery of practices related to learning and application of statistical software R for problem solving in the field of digital information management (20% of the overall grade), in addition to the delivery of one and / or several works of application of statistics for the resolution of case studies in library information sciense (alternatively may be tasks of revision or extension of the subject) which represents 40% of the final grade. Second chance evaluation The evaluation will be done following the same procedure as in the first opportunity. Early exam session All these remarks are applied to the early exam session. "No presentado" grade For any of the two opportunities to pass the subject, the "NO PRESENTADO" grade will be given to the students who did non take the objective final test. Students with recognition of part-time dedication and/or academic exemption of attendance In the case of students with recognition of part-time dedication and/or academic exemption of attendance that decides not to attend classes, they will be evaluated in the two opportunities as the rest of the students who are in a similar situation. Fraud in tests or evaluation activities will directly imply the failure grade "0" in the subject in the corresponding call, thus invalidating any grade obtained in all the evaluation activities for the extraordinary call. |
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| Sources of information |
| Basic |
Everitt, B. y Hothorn, T. (2011). An Introduction to Applied Multivariate Analysis with R. Springer-Verlag New York
Daniel Peña (2002). Análisis de datos multivariantes. S.A. MCGRAW-HILL / INTERAMERICANA DE ESPAÑA
Cao, R., Francisco, M., Naya, S., Presedo, M.A., Vázquez, M., Vilar, J.A. y Vilar, J.M. (2001). Introducción a la Estadística y sus aplicaciones. Pirámide
Egghe, L. y Rousseau, R. (1990). Introduction to Infometrics. Quantitative Methods in Library, Documentation and Information Science. Amsterdam: Elsevier |
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| Complementary |
Daniel Zelterman (2015). Applied Multivariate Statistics with R. Springer International Publishing
Cástor Guisande, Antonio Vaamonde (2012). Gráficos estadísticos y mapas con R. Díaz de Santos
Vélez, R. & García, A. (1993). Principios de Inferencia Estadística. UNED |
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| Recommendations | |
| Subjects that it is recommended to have taken before | |
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| Subjects that are recommended to be taken simultaneously |
| Subjects that continue the syllabus | |
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| Other comments | |
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Para axudar a conseguir unha contorna inmediata sostida e cumprir co obxectivo da acción número 5: “Docencia e investigación saudable e sustentable ambiental e social” do "Plan de Acción Green Campus Ferrol: A entrega dos traballos documentais que se realicen nesta materia: • Solicitaranse en formato virtual e/ou soporte informático. • Realizarase a través de Moodle, en formato dixital sen necesidade de imprimilos. • En caso de ser necesario realizalos en papel: - Non se empregarán plásticos. - Realizaranse impresións a dobre cara. - Empregarase papel reciclado. - Evitarase a impresión de borradores. • Débese de facer un uso sustentable  dos recursos e a prevención de impactos negativos sobre o medio natural. • Traballarase para identificar e modificar prexuízos e actitudes sexistas, e influirase na contorna para modificalos e fomentar valores de respecto e igualdade. • Deberanse detectar situacións de discriminación e propoñeranse accións e medidas para corrixilas. |