Syllabus
1. Random event with finitely many outcomes, classical probability and axiomatic definition.
2. Geometric probability.
3. Independence of random events, conditional probability, Bayes' theorem.
4. Discrete random variable, its distribution, expectation, variance.
5. Correlation, causality.
6. Hypotheses testing.
Annotation
Introduction to discrete probability and solutions of interesting problems by simple probabilistic and statistical methods. An elective course for 1st year students of General and Financial Mathematics.