Introduction to Programming with R (19151)

- Knowledge of the general principles of analytical design, graphical elements and their visual perception. - Ability to select the type of representation and graphic elements most appropriate to the type of data and the result to be communicated. - Ability to read, understand, analyze and elaborate graphic representations with social data. - Ability to produce automated reports and dashboards with reproducible visualizations.

1. Fundamentals of graphical practice 1.1. Why graphics 1.2. Graphical integrity 1.3. Graphical perception 1.4. Principles of graphical representation 2. The grammar of graphs in R 2.1. Building graphs layer by layer 2.2. Guides and scales 2.3. Coordinate systems 2.4. Facets 2.5. Themes 3. Data visualization in R 3.1. Distribution 3.2. Correlation 3.3. Ranking 3.4. Part of a whole 3.5. Evolution 3.6. Maps 3.7. Flow 3.8. Other techniques 4. Data communication in R 4.1. R Markdown 4.2. Documents and notebooks 4.3. Presentations 4.4. Other formats 4.5. Dashboards

Training Activities: - Theoretical-practical classes - Tutorials - Group work - Individual student work Teaching Methods: - Presentations in the professor's lecture room with computer and audiovisual support, in which the main concepts of the subject are developed and a bibliography is provided to complement the students' learning. - Critical reading of texts recommended by the subject professor: Press articles, reports, manuals and/or academic articles, either for later discussion in class, or to expand and consolidate knowledge of the subject. - Resolution of practical cases, problems, etc. raised by the professor, either individually or in a group. - Presentation and discussion in class, under the moderation of the professor, of topics related to the content of the subject, as well as practical case studies. - Developing pieces of work and reports, individually or in group.