MAT-01566 Mathematics 5, 5 cr

Person responsible

Henri Hansen


Implementation Period Person responsible Requirements
MAT-01566 2019-01 4 Henri Hansen
Final Exam and weekly exercises

Learning Outcomes

In this course, the students learn the basic concepts of probabilities, random variables and random vectors. The students learn to compute discrete and continuous probabilities and expectation values such as variances and correlations. The students also learn to apply the probability calculus to practical problems. The students learn how to justify their claims using mathematical methods and to present their solutions orally as well as in written form.


Content Core content Complementary knowledge Specialist knowledge
1. Basic Notions of Probability Theory: Probability and Expectation, Conditional Probability, Total probability and Independence  Bayesian probability and Combinatorial analysis.   
2. Random Variables: The Probability Mass and Density Functions, Important Discrete Random Variables, Important Continuous Random Variables and Expectation and Variance  Moment Generating Function   
3. Random Vectors: Discrete and Continuous Random Vectors, Covariance and Correlation, Multinormal Distribution   Transformations of Random Vectors   
4. Sampling distributions and statistical inference: Statistics and sampling distribution, The Central Limit Theorem, prediction intervals, test of statistical hypotheses     

Instructions for students on how to achieve the learning outcomes

The grade of the course is based on the final exam and exercises.

Assessment scale:

Numerical evaluation scale (0-5)

Partial passing:

Completion parts must belong to the same implementation


Course Mandatory/Advisable Description
MAT-01366 Mathematics 3 Mandatory    

Correspondence of content

Course Corresponds course  Description 
MAT-01566 Mathematics 5, 5 cr MAT-01560 Mathematics 5, 5 cr  

Updated by: Kunnari Jaana, 05.03.2019