Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Introduces key concepts in probability and statistics, illustrating their application through various examples and emphasizing the importance of mathematical language in understanding the universe.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Covers fundamental concepts in probability and statistics, including the law of total probability, Bayes' theorem, and independence of events.
