Competencies and objectives
Course context for academic year 2020-21
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. Background on probability and statistical inference will be helpful but not requiered.
Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2020-21
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 skills relevant to the field of study.
- CGUA3 : Acquire or possess basic Information and Communications Technology skills and correctly manage the information gathered.
Generic Degree Course Competences
- CG1 : Develop the capacity for analysis, synthesis and critical reasoning.
- CG2 : Show the capacity for effective and efficient management/direction: entrepreneurial spirit, initiative, creativity, organisation, planning, control, decision making and negotiation.
- CG3 : Solve problems effectively.
- CG4 : Show capacity for teamwork.
- CG5 : Commitment to ethics, the values of equality and social responsibility as a citizen and professional.
- CG6 : Self-learning.
- CG7 : Show the capacity to adapt to new situations.
- CG9 : Show 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 2020-21
- 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
General
Code:
25070
Lecturer responsible:
TROTTINI, MARIO
Credits ECTS:
6,00
Theoretical credits:
1,12
Practical credits:
1,28
Distance-base hours:
3,60
Departments involved
-
Dept:
MATHEMATICS
Area: STATISTICS AND OPERATIONS RESEARCH
Theoretical credits: 1,12
Practical credits: 1,28
This Dept. is responsible for the course.
This Dept. is responsible for the final mark record.
Study programmes where this course is taught
-
DEGREE IN MATHEMATICS
Course type: OPTIONAL (Year: 4)