After completing the course, the student is expected to
be familiar with, and be able to use, different probability concepts and symbols that are often used in statistics
know the mathematical foundations for the probability models that form the foundation for statistical inference
have thorough knowledge of univariate and multivariate probability distributions
have knowledge of moments and moment-generating functions
have knowledge of different concepts of convergence
The axiomatic foundation for probability theory. Combinatorics. Multivariate random variables. Conditional probability distributions. Moments and momen-generating functions. Order statistics. The multivariate normal distribution. Different concepts of convergence. Central limit theorems.
Instruction is given in form of lectures.
The examination takes place through a written examination at the end of the course and through written presentations of take-home assignments.