Entry requirements

180 credits including 5 credits in statistics

Learning outcomes

Leaning Outcomes

After completing the course, a student is expected to:

* have obtained basic knowledge of the programming language R

* be able to load, process and describe data in R

* be familiar with visualization of data with the help of R

* be able to independently implement simple algorithms and simulations in R

* be able to write and interpret simpler program code

* have an understanding for the types of problems that data analysis and computers are suitable for solving

Content

Content

The course covers basic data management in R, such as importing data, data cleaning and handling of data in vectors, matrices and "data frames". The course also covers description, tables and visualization of data. The course introduces fundamental programming with functions, vectorization, loops, control structures (such as if-clauses, while- and for-loops) and Monte Carlo simulation.

Instruction

Instruction

Teaching is given in the form of lectures, computer exercises and seminars.

Assessment

Assessment

The examination takes place partly through a written examination at the end of the course and through presentation orally and in writing of compulsory home assignments. If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.