Confidence Intervals: Margins, Coverage, Pivots

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Explores parameter estimation, standard errors, and confidence intervals using the central limit theorem and practical examples.

Explores hypothesis testing using Wilks' Theorem, likelihood ratio statistics, p-values, interval estimation, and confidence regions.

Explores constructing confidence intervals and MLE limit theorems for large samples.

Covers the construction of confidence intervals and approximate critical values in statistical inference.

Explains confidence intervals, margin of error, pivots, and significant figures in statistical estimation.

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

Covers computation and estimation in stochastic simulation, focusing on generating iid replicas and optimal importance sampling.

Covers the calculation of paired t-tests, advantages/disadvantages of different t-tests, and the concept of ANOVA.

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