Equidistribution of CM Points

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

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

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Explores joint random variables, conditional density, and independence in probability and statistics.

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

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Explores conditional density, expectations, and independence of random variables with practical examples.

Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

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

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.