Multivariate random variable

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Related lectures (30)

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Probability and Statistics: Fundamental Theorems

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

Statistical Theory: Fundamentals

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Random Variables: Expectation and Independence

Explores random variables, expectation, and independence in probability theory.

Probabilities and Statistics: Key Theorems and Applications

Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Independence and Covariance

Explores independence and covariance between random variables, discussing their implications and calculation methods.

Law of Large Numbers: Strong Convergence

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

Central Limit Theorem: Properties and Applications

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

Transformations of Random Variables

Covers the pdf of the sum of continuous random variables, convolution, and transformations like Y=aX.

Random Variables: Basics

Introduces random variables, probability measurement, expectation, moments, and relations between random variables.