7.5 credits cr.
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This course deepens your knowledge in statistical programming. The course provides tools useful in design of statistical surveys, estimation, hypothesis testing and Bayesian analysis. The course presents some basic principles for numerical computing, numerical matrix algebra, solutions to equations, function optimization, and simulation techniques
This course gives you knowledge about the basic principles of numerical computing. You will learn how to design and organize algorithms for function optimization, integration and simulation of distributions and how to solve statistical computing problems with help of statistical software. You will also learn how to carry out simulation experiments.
The course is given at day time, full time.
The course forms a part of the Master's Program in Statistics, but it can also be studied as a freestanding course.
The teaching forms consists of lectures and computer labs. The course is given in English.
- Course description, vt-22 (420 Kb)
More information for registered students will be found in Athena.
Examination will be in the form of a written test and a written hand in assignment.
ScheduleThe 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.
Course literatureNote that the course literature can be changed up to two months before the start of the course.
Teachers Spring semester 2022
You will find Frank's reception hours in the link above. If you wish to visit Frank outside of his reception hours, you are welcome to e-mail her for an appointment.
If you have questions about studying at the Department of Statistics, please contact our study- and career counselor.