Fundamentals of Probability Theory 2018
Tutorials :
Tutorial 1 Countable and uncountable sets, Sigma-algebra, (Probability) measure; Appendix on Set identities
Tutorial 2 (Probability) measures, Useful properties of measures/ Sigma-algebras, Independence, d-systems & \pi-systems
Tutorial 3 Measurable functions (random variables), Borel-Cantelli Lemma and applications
Tutorial 4 Modes of Convergence (in measure VS almost everywhere), Vista : Convergence Diagram, Independence II : Random Variables
Tutorial 5 Lebesgue theory of integration, Monotone Convergence Theorem and Dominated Convergence Theorem
Tutorial 6 Probability density and distribution functions of a random variable (reviews : uniform, exponential and normal distributions)
Tutorial 7 Sigma-finiteness, product measures, Fubini's theorem, Markov's inequality : existence of higher moments
Tutorial 8 Characteristic functions (Fourier transforms of density functions), (Strong/Weak) Laws of large numbers
Tutorial 9 Gaussian random variables on R^n, Convergence in distribution (weak convergence), relation with convergence in probability
Tutorial 10 (Substituted by Tomasz Kosmala) Central Limit Theorem, Conditional probability and expectation