Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
