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Covers the optimal statistical tests for exponential families and the use of approximations in hypothesis testing.

Explores the theory and applications of likelihood ratio tests in statistical hypothesis testing.

Explores hypothesis testing, Wilks' theorem, p-values, confidence intervals, and pivotal quantities.

Covers the systematic derivation of a synchronization algorithm with a generalized likelihood test in wireless receivers.

Covers likelihood ratio statistic, confidence intervals, and hypothesis testing concepts.

Introduces stochastic simulation fundamentals, covering course organization, queueing models, finance, statistics, physics, and exam details.

Covers iterative weighted least squares, Poisson regression, mixed models, and likelihood ratio statistic.

Covers the stochastic simulations course, G/G/1 queueing model, computational finance, statistics, physics, and Bayesian inference.

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.