Extreme Values: Applications and Probability Framework

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Estimators and Confidence Intervals

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Statistical Analysis of Extremes: Risk Measures & Inference

Explores risk measures, inference techniques, and statistical analysis of extreme values.

Confidence Intervals and Hypothesis Tests

Covers confidence intervals, hypothesis tests, standard errors, statistical models, likelihood, Bayesian inference, ROC curve, Pearson statistic, goodness of fit tests, and power of tests.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Introduction to Continuous Random Variables: Probability Distributions

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Estimating Moments: GEV and GPD

Explores moment estimation in GEV and GPD models, including L-moment estimation and robust parameter estimation.

Continuous Random Variables

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Linear Combinations: Moment-Generating Functions

Explores moment-generating functions, linear combinations, and normality of random variables.

Probability Distributions: Central Limit Theorem and Applications

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Probability and Statistics

Covers probability distributions, moments, and continuous random variables.