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.
Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
Covers the properties and construction of Poisson processes from i.i.d. Exp(X) random variables, emphasizing the importance of the process rate and jump time distributions.
Explores independence and covariance between random variables, discussing their implications and calculation methods.
Explores Poisson processes through examples and proofs, discussing customer arrivals in a store and related probabilities.
