Selected statistical methods with applications


The course contains 2-4 (depending on the course occasion) selected statistical areas/themes which are determined before each course occasion. The areas/themes have normally not been dealt with during previous courses (or only to a limited extent). The course is intended to broadening the students' knowledge in statistics, provide good examples of current statistical method and give inspiration for subjects for the bachelor thesis.

Examples of areas/themes that could be included in the course are missing data, survival analysis, text analysis, bayesian methods and introduction to machine learning. Other themes can also be included in the course.

For each area/theme, the course relates theory to practice by alternating theoretical lectures, practical exercises and programming. A central element is the students' independent work with a number of problems (case studies), which are presented in both written and oral presentations.

The course is given at day time, half time.


Teaching Format

The teaching forms consist of lectures and exercises.

Course information

Course description vt-26 pdf, 162.3 kB. (205 Kb)

Teachers spring 2026

Edgar Bueno

Dan Hedlin

Gebregengus Ghilagaber

You will find the teachers reception hours in the link above. If you want to visit the teachers outside of their reception hours, you are welcome to e-mail them for an appointment.

Assessment

Examination will be in the form of written assignments and oral presentations.


The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.


Note that the course literature can be changed up to two months before the start of the course.


Course reports are displayed for the three most recent course instances.