Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
