Numerical Simulation of SDEs: Monte Carlo & Optimal Control

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Confidence Intervals: Student, Asymptotic Wald

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Estimating Parameters: Confidence Intervals

Explores estimating parameters through confidence intervals in linear regression and statistics.

Networked Control Systems: Stability Analysis and Examples

Explores the impact of delays and sampling on networked control systems' stability, with examples and simulations.

Variance Reduction Techniques

Covers variance reduction techniques in stochastic simulation to improve output quantity estimation accuracy.

Basics of linear regression model

Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.

Hypothesis Testing and Confidence Intervals: Key Concepts

Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.

Interval Estimation

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Statistical Tests: T-Tests and ANOVA

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

Confidence Intervals and MLE Limit Theorems

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