Project in Statistics
This project course on advanced statistical modeling is a compulsory part of the MSc program in statistics. The content of the course presumes a mathematical level corresponding to this MSc program, and consists of:
- An advanced subject in statistical modeling.
- Independent literature studies.
- Theoretical work on models and methods relevant for data analysis.
- Practical work on statistical modeling, implementation and/or data analysis.
- Organization of a larger project and writing of reports.
- Written presentation of methodology, data analysis and results.
The exact subjects and how the different components above are weighed depend on the supervisors assigned to the course. At the beginning of the course, all offered projects will briefly be presented and course participants asked to indicate a prioritised list of which project they wish to work on. Course participants will then be assigned to a project based on their indicated preferences. Students can only work on one of the offered projects and cannot bring their own projects to work on as part of this course.
Examples of advanced subjects are:
- Classification and machine learning.
- High-dimensional statistics.
- Functional data analysis.
- Bayesian analysis and Markov Chain Monte Carlo (MCMC).
- Mixed and hierarchical models.
- Graphical models.
- Applied biostatistics.
- Causal inference.
- Dynamical systems.
MSc Programme in Mathematics-Economics
MSc Programme in Statistics
Project under supervision.
The participants are expected to have the mathematical and
statistical competences of a MSc student in statistics and have
passed the course Regression (Reg).
Academic qualifications equivalent to a BSc degree is recommended.
This course is reserved for students in the MSc Programme in Mathematics-Economics and the MSc Programme in Statistics.
- 7,5 ECTS
- Type of assessment
- Type of assessment details
- Final individual report
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
Criteria for exam assessment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
- Project work
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 4
- No limit
The number of seats may be reduced in the late registration period
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Sebastian Weichwald (10-767a686c666b7a646f67437064776b316e7831676e)
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Courseinformation of students