Entry requirements

A Bachelor's degree of 180 credits with at least 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.