Martingales: More Theory

Related lectures (30)

Page 2 of 3

Explores the Poisson Paradigm and dependency measures in ordered pairs and graphs.

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.

Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.

Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.

Explores the construction of Ramanujan graphs using polynomials and addresses challenges with the probabilistic method.

Explores the FKG inequality in percolation theory and the reverse FKG theorem.

Covers probabilistic methods in combinatorics, monochromatic edges, 2-colorable graphs, and good 2-colorings.