Delves into the duality between confidence intervals and hypothesis tests, emphasizing the importance of precision and accuracy in estimation.
Explores the distribution theory of least squares estimators in a Gaussian linear model, focusing on precision and confidence intervals construction.
Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Discusses Monte Carlo VaR accuracy, confidence intervals, backtesting, and multivariate distributions.
