Random Permutations and Probabilities

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.

Covers jacamar data analysis, smoking data models, and challenges with log-linear models in visual impairment data.

Delves into probability, statistics, random experiments, and statistical inference, with practical examples and insights.