Lectures related to Normality test

Gaussian Linear Regression: Assumptions and Residuals

Explores the assumptions and checking methods for Gaussian linear regression models using residuals and graphical plots.

Quantitative Risk Management: VaR Estimation and Multivariate Distributions

Explores VaR estimation, confidence intervals, backtesting, multivariate distributions, and normality testing through QQ plots and the Jarque-Bera statistic.

Multivariate Normal Distribution: Correlation and Covariance

Covers correlation, covariance, empirical estimates, eigenvalues, normality testing, and factor models.

Regression Diagnostics

Covers regression diagnostics for linear models, emphasizing the importance of checking assumptions and identifying outliers and influential observations.

Data Exploration: Normal Distribution

Explores data distribution strategies, normal modeling, and checking normality with graphical tools.

Statistical Hypothesis Testing

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