Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
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.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
