Lectures related to Equidistribution of CM Points

Explores toy models, sigma-algebras, T-valued random variables, measures, and independence in probability theory.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.

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

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

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