Optimal Selling Strategy

Related lectures (30)

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Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Covers probability distributions, moments, and continuous random variables.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Explores recurrence and transience in Markov chains, discussing the strong Markov property and state classifications.

Covers inequalities, joint Gaussian distribution, risk estimation, and classification method testing in probability and statistics.

Explores Markov chains, transition matrices, distribution, and random walks.

Explores the convergence of random variables, the law of large numbers, and the distribution of failure time.

Explores different modes of convergence for random variables.