Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Introduces fundamental probability concepts, including events, complements, conditional probability, and random variables.
Introduces key concepts in probability and statistics, illustrating their application through various examples and emphasizing the importance of mathematical language in understanding the universe.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
