Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.
Explores extreme values in random variables, applications in environmental factors, reliability modeling, block maxima distribution, and the Generalized Extreme Value distribution.
Explores variance reduction techniques in stochastic simulation, emphasizing the use of auxiliary random variables and sample averages to improve efficiency.
