TILM3618 Introduction to Computational Statistics (3 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
Be familiar with computational statistics methods with examples. The course examines, among other things, the simulation type approach to various statistical problems, the Monte Carlo error, and the bootstrap method.
Learning outcomes
Student will become familiar with the basics of computational statistics methods.
Additional information
The course is held every year. Students majoring in statistics can complete the course already in the third academic year (B.Sc. phase) before starting advanced studies, where many courses make use of the methods of this course.
If you wish to complete the course in English, please contact the person in charge of the course.
Description of prerequisites
Knowledge on statistical inference (intermediate level courses TILM3561 and TILM3707). A short summary on the essential topics in those courses is given in TILM3627/TILM3597 Statistical learning: Boot camp.
In addition, some statistical programming course, such as TILM3708 Statistical Programming and Visualisation.