Confidence Intervals and MLE Limit Theorems

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Page 3 of 3

Covers the theory of sampling, focusing on statistics for mathematicians.

Introduces multivariate statistics, covering normal distribution properties and characteristic functions.

Explores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Presents the proof of the Central Limit Theorem using Lindeberg's principle.

Explores the Central Limit Theorem and its statistical implications in random variables.

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

Covers the Likelihood Ratio Test and hypothesis testing methods using Maximum Likelihood Estimators.

Explores the distribution theory of least squares estimators in a Gaussian linear model.

Covers hypothesis testing, confidence intervals, and their applications in statistics.