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) |
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.
Examples of study plans
Four examples are shown: two focusing on statistical modelling for stochastic differential equations and two focusing on statistical modelling for data science. Both include study plans for students beginning in September or in February.
The study plans are examples only. Students are free to exchange the shown courses with other courses if the general requirements for the curriculum in mathmatical modelling and computation and the specialisation are satisfied. The proposed plans fulfil requirements of the MMC curriculum.
A few programme specific courses in excess of the required 50 ECTS are here included and these will count as electives.
Study plans with focus on statistical modelling for stochastic differential equations - September start
Quantitative methods to assess... Quantitative methods to assess sustainability (Polytechnical Foundation)
Non-linear random effect models:... Non-linear random effect models: time-independent and dynamic models
Study plans with focus on statistical modelling for stochastic differential equations - February start
Quantitative methods to assess... Quantitative methods to assess sustainability (Polytechnical Foundation)
Innovation in Engineering (Polytechnical... Innovation in Engineering (Polytechnical Foundation)
Non-linear random effect models:... Non-linear random effect models: time-independent and dynamic models
Study plans with focus on statistical modelling for data science - September start
Study plans with focus on statistical modelling for data science - February start
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.
Contact
Jan Kloppenborg Møller Associate Professor Phone: +45 45253418 jkmo@dtu.dk
Bo Friis Nielsen Professor, Head of Section Phone: +45 45253397 bfni@dtu.dk