Continuous Random VariablesExplores continuous random variables, density functions, joint variables, independence, and conditional densities.
Probability and StatisticsCovers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Copulas: Properties and ApplicationsCovers copulas, Sklar's Theorem, meta distributions, and various dependence measures like rank correlations and coefficients of tail dependence.
Continuous Random VariablesCovers continuous random variables, probability density functions, and distributions, with practical examples.
Maximum Likelihood EstimationCovers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.