Birth & Death Chains: Analysis & Probabilities

Related lectures (29)

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Covers the criterion for recurrence in infinite chains based on the expected number of visits in a state.

Covers the theory and applications of Markov chains in modeling random phenomena and decision-making under uncertainty.

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

Covers the interpretation of the Lindblad equation and its unitary part in quantum gases.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Explores the Bonus Malus system for insurance premiums and Markov chain transition probabilities.

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

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

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

Explores Markov chains' properties, expectations, and recurrence in Poisson processes.