Lectures related to Probabilistic Methods in Combinatorics

Interlacing Families and Ramanujan Graphs

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Probability and Statistics: Fundamentals

Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.

Independence Polynomial of Dependency Graph

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

Graph Theory and Network Flows

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Probability and Statistics: Fundamental Theorems

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Conditional Probability: Basics and Examples

Explains conditional probability through dice and coin examples.

Continuous Random Variables

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.