Statistical Programming with R
7.5 credits
Syllabus, Master's level, 2ST105
A revised version of the syllabus is available.
- Code
- 2ST105
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Statistics A1N
- Grading system
- Fail (U), Pass (G), Pass with distinction (VG)
- Finalised by
- The Department Board, 15 October 2021
- Responsible department
- Department of Statistics
Entry requirements
120 credits including 90 credits in statistics
Learning outcomes
After completing the course, the student is expected to
- be able to use and program in the programming language R
- be able to implement simple algorithms in R independently
- have developed good habits in programming in R to ensure efficient and safe code in order to facilitate collaborations
- be familiar with data visualization techniques in R
- be able to use R to solve statistical problems, including data handling and data analysis
- understand the foundations of and be able to design and describe simulation studies
Content
Concepts and basic definitions in programming, arrays, matrices and data frames, the usage and definitions of procedures, functions and packages, vectorization, loops, control structures (if, while, for), importing data, visualization of data, simulation studies, Latex.
Instruction
Teaching is given in the form of lectures, labs and/ or as seminars.
Assessment
The examination takes place through a written examination at the end of the course and/or through written and/or oral presentation of compulsory assignments.