Degree | Type | Year | Semester |
---|---|---|---|
2503852 Applied Statistics | OB | 3 | 1 |
It is advisable to have knowledge on probability, statistical inference and linear models.
This course aims to introduce students to time series models and their applications. A time series is a set of observations of a random phenomenon evolving over time (or any other ordered magnitude). Time series appear in many fields of application. Therefore, their analysis and the modelling of the underlying random phenomena are of crucial theoretical and applied importance. The ultimate goal is the modelling of the mechanism that generates the data, performing model diagnostics, and predicting future values.
Unless the requirements enforced by the health authorities demand a prioritization or reduction of these contents.
During the theoretical lessons (2 H/week) the fundamental results will be presented, and computer exercises will be developed. During the lab hours (with laptop) students will solve real data problems. The programing language used is R.
The proposed teaching methodology may experience some modifications depending on the restrictions on face-to-face activities enforced by health authorities
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Practical sessions | 26 | 1.04 | 2, 1, 3, 12, 4, 5, 19, 17, 6, 7, 8, 11, 10, 16, 14, 15, 13, 18, 20 |
Theoretical sessions | 26 | 1.04 | 2, 1, 3, 5, 19, 17, 6, 7, 8, 11, 14, 15, 13, 9, 18, 20 |
Type: Autonomous | |||
Personal work | 60 | 2.4 | 2, 1, 3, 12, 4, 5, 19, 17, 6, 7, 8, 11, 10, 16, 14, 15, 13, 9, 18, 20 |
Real data analysis | 25 | 1 | 2, 1, 3, 12, 4, 5, 19, 17, 6, 7, 8, 11, 10, 16, 14, 15, 13, 9, 18, 20 |
During the course, students must handle computer labs. There will be mid-term and final exams that will include both theoretical and practical questions. To be eligible for the resit exam, you must get a minimum of 3/10 in practice and theory.
Student’s assessment may experience some modifications depending on the restrictions on face-to-face activities enforced by health authorities
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Final Exam | 0,4 | 3 | 0.12 | 2, 1, 3, 5, 6, 7, 8, 11, 16, 13, 18, 20 |
Homework (exercises and computer activities) | 0,3 | 8 | 0.32 | 2, 1, 3, 12, 4, 5, 19, 17, 6, 7, 8, 11, 10, 16, 14, 15, 13, 9, 18, 20 |
Mid-term exam | 0,3 | 2 | 0.08 | 2, 1, 3, 5, 6, 7, 8, 11, 16, 13, 18, 20 |
R Core Team (2021). R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. URL
https://www.R-project.org/.
We shall use several R libraries, including forecast, TSA, TSeries, quantmod, fgarch, tscount.