Delves into probability, statistics, random experiments, and statistical inference, with practical examples and insights.
Introduces random variables, probability distributions, and expected values through practical examples.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.