Multinomial Distribution

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Covers probability distributions, moments, and continuous random variables.

Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.

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

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Explores moment-generating functions, linear combinations, and normality of random variables.

Covers the normal distribution, including its properties and calculations.

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

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

Explores different modes of convergence for random variables.

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