Algebra of random variables

Related lectures (31)

Introduces the basics of conditional expectation, covering definitions, properties, and examples in the context of random variables.

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Covers the fundamentals of probabilities, including independence, conditional probabilities, and random variables.

Explores conditional expectation, the grouping lemma, and the law of large numbers.

Covers conditional expectation, convergence of random variables, and the strong law of large numbers.

Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.

Discusses variance and covariance calculations, transformations of random variables, and mixtures in probability and statistics.

Covers the concept of variance for random variables and introduces calculation rules.

Covers free fields and probabilistic functions, focusing on random variables and their properties.

Covers random variables, probability functions, expectations, variances, and joint distributions.

Covers common distributions, moment generating functions, and covariance matrices in statistics for data science.

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