Law of large numbers

Related lectures (30)

Page 3 of 3

Covers the Monte Carlo method for generating realizations and unbiased estimators.

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

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

Covers fundamental statistics concepts, including estimation theory, distributions, and the law of large numbers, with practical examples.

Explores Kolmogorov's 0-1 law, showcasing cases of convergence and divergence in random variables based on the finiteness of expectations.

Explains message passing in networks, emphasizing probabilities and average edges between communities.

Explores the convergence of averages of random variables and empirical frequencies in probability theory.

Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.

Covers the properties and error estimates of the Monte Carlo method in stochastic simulation.

Covers the Poisson process, a stochastic model for communications, focusing on the probability law.