Probability MAT2106

Course content:combinatorics, axioms of probability theory, probability space, classical definition of probability, conditional probability, Bayes formula, some schemes in probability (Bernoullie, Poisson, Pascal, Polya), one dimensional distributions and their parameters, normal distribution, mixed and truncated distribution, two-dimensional distribution, compositions of distributions, normal distribution on the plane, characteristic functions, central limits theorems, great number laws.

Learning outcomes:calculating probability and parameters of distributions, analysis of experyments, particularly Bernoullie type, understanding and interpretation of limits and central limits theorems