Statistical Modelling - Specialization
Statistical Modelling
Statistics and statistical modelling are present in most engineering applications, e.g. medicine, forecasting renewable energy production, control of industrial processes, financial engineering, etc. The specialization includes statistical modelling of stochastic dynamical systems (time series analysis), probability theory and statistical inference for controlled experiments. The specialization provides the theoretical foundation for advanced statistical modelling as well as practical experience with applied statistical modelling.
Prereqisites: It is strongly recommended that the student have basic knowledge of statistical modelling and probability theory corresponding to 02418 and 02405 before entering the master program. In addition it is recommended that the student have basic knowledge of linear time series analysis and design of experiments corresponding to 02417 and 02411.
Specialization specific courses
The student must follow the requirements in the general curriculum for the programme. In addition, at least 20 ECTS points are obtained among the following courses:
| 02407 | Stochastic Processes - Probability 2 | 5 | point | Autumn E3A (Tues 8-12) |
| 02426 | Non-linear random effect models: time-independent and dynamic models | 5 | point | Spring F4B (Fri 8-12) |
| 02427 | Advanced Time Series Analysis | 10 | point | Autumn E5 (Wed 8-17) |
| 02429 | Analysis of correlated data: Mixed linear models | 5 | point | Autumn E2B (Thurs 8-12) |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
Recommended elective courses
The following courses are recommended for the specialization:
| 02586 | Statistical Genetics | 5 | point | Autumn E5B (Wed 13-17) |
Connection to other speciliazation: The statistical modelling specialization is naturally combined with a number of other specializations. Below are some recommendations.
Machine learning: Machine learning and statistical modelling are highly related, and it is natural to combine statistical modelling with courses from the machine learning specialization, e.g. 02458, 02471, 02477 and 42186.
Dynamical systems: Students that want to specialize in statistical modelling of stochastic dynamical systems should combine the specialization with courses from “applied mathematical analysis” or “computational modelling and simulation”, e.g. 01622, 01257, 02425, 02627, 02421 and 02616.
Operation research and optimization: Students that aim at applying statistical modelling decision making and optimal control should combine the specialization with courses from the operation research and optimization specialization, e.g. 02611, 02435 and 02428.
Specializations are merely recommended ways of choosing the courses in the curriculum. Applicants are not admitted to a specialization but to the programme and it is possible to choose among all the courses in the curriculum following the directions given. However, if a specialization has been fulfilled the title of the specialization may be added to the diploma.