Competencies and objectives
- Course context for academic year 2021-22
- Course content (verified by ANECA in official undergraduate and Master’s degrees)
- Learning outcomes (Training objectives)
- Specific objectives stated by the academic staff for academic year 2021-22
Course context for academic year 2021-22
Time series is an optional subject in the itinerary of Mathematics applied to Social Sciences. The objective of the course is to provide an introduction to time series models for univariate time series data. In particular, we will study the class of AutoRegressive Integrated Moving Average (ARIMA) models. Within this class, we will cover the problems of model identification, estimation, selection and model diagnosis and prediction. For computation, visualization and analysis of time series data we will use the free software R. This course assumes knowledge of probability theory and statistical theory (at the level taught in the probability and statistical inference courses 25026 and 25035). Background on linear regression methods and familiarity with the statistical software R will be helpful but not requiered.
Course content (verified by ANECA in official undergraduate and Master’s degrees)
Specific Competences (CE)
- CE10 : Communicate, both orally and in writing, mathematical knowledge, procedures, results and ideas.
- CE11 : Ability to solve academic, technical, financial and social problems using mathematical methods.
- CE12 : Ability to work in a team, providing mathematical models adapted to the needs of the group.
- CE15 : Recognise and analyse new problems and prepare strategies to resolve them.
- CE5 : Propose, analyse, validate and interpret models of simple real-life situations, using the most appropriate mathematical tools for the purpose.
- CE6 : Solve mathematical problems using basic calculus skills and other techniques, planning their resolution according to the tools available and any time and resource restriction.
- CE7 : Use computer applications for statistical analysis, numerical calculus and symbolic calculus, graphic visualisation and others to experiment in Mathematics and solve problems.
- CE9 : Use bibliographic search tools for Mathematics.
Specific Generic UA Competences
- CGUA1 : Understand scientific English.
- CGUA2 : Possess computer knowledge related to the field of study.
- CGUA3 : Acquire or posses basic ICT (Information and Communication technology) skills and manage the information obtained appropriately.
Generic Degree Course Competences
- CG1 : Develop the capacity for analysis, synthesis and critical reasoning.
- CG2 : Show the ability for effective and efficient direction/management: entrepreneurial spirit, creativity, organisation, planning, control, decision making and negotiation.
- CG3 : Resolve problems effectively.
- CG4 : Show ability for teamwork.
- CG5 : Commitment to ethics, the values of equality and social responsibility as a citizen and as a professional.
- CG6 : Learn autonomously.
- CG7 : Show the ability to adapt to new situations.
- CG9 : Demonstrate the ability to transmit information, ideas, problems and solutions to both specialist and non-specialist audiences.
Learning outcomes (Training objectives)
No data
Specific objectives stated by the academic staff for academic year 2021-22
- Learn how to build, estimate and validate ARIMA time series models for univariate time series data
- Learn how to use ARIMA models for time series forecasting
- Utilize R for computation, visualization and analysis of time series data
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