Data Programming (19138) Statistics and Data Science I (19140) Statistics and Data Science II (19141) Survey Research Methodology I (19137)

- Ability to analyze survey data. - Ability to solve frequent problems in survey analysis, such as dealing with missing cases. - Ability to work with aggregate, multilevel and longitudinal data.

1. Survey Data Analysis 1.1. Operationalization and data cleaning 1.2. Cross-sectional data analysis 1.3. Panel data analysis 1.4. Multilevel analysis 2. The use of survey data in forecasting 2.1. Predicting versus explaining 2.2. Performance evaluación 3. Dealing with missing data 3.1. Complete case analysis 3.2. Mean/median substitution 3.3. Multiple imputation 4. Data reporting 5. Work examples 5.1. Implementation of acquired knowledge to the analysis of social reality, in line with the Sustainable Development Goal on gender equality, equity, and non-discrimination.

Training Activities: - Theoretical-practical classes - Group work - Individual student work - Partial and final examinations 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.