7.5 ECTS credits
The course covers the concept of probability, independent events, conditional probabilities, stochastic variables, mathematical expectation value, variance, some statistical standard distributions, and the central limit theorem as well as practical applications of the above. The course also covers descriptive statistics, linear relations between two variables, estimation and hypothesis testing, random numbers, and simulation. Instruction is partly in the form of computer lab sessions with statistical software programmes.
Progressive specialisation: G1N (has only upper‐secondary level entry requirements)
Education level: Undergraduate level
Admission requirements: General admission requirements plus either - field-specific eligibility A8 (upper secondary school level Physics 2, Chemistry 1, Mathematics 3c), barring Physics 2 and Chemistry 1, or - field-specific eligibility 8 (upper secondary school level Physics B, Chemistry A, Mathematics D), barring Physics B and Chemistry A.
Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.
This course is included in the following programme
- Study Programme in IT-Design: Software Design (studied during year 2)
- Master of Science in Industrial Engineering and Management (studied during year 2)
- Study Programme in Engineering - Computer Science (studied during year 2)
- Bachelor Programme in Computer Science (studied during year 2)