Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.
Covers random vectors, joint probability density, independent random variables, functions of two random variables, and Gaussian random variables.
Explores the convolution of random variables, discussing sums of independent variables and their distributions in discrete and continuous contexts.
