Covers fundamental concepts in probability and statistics, including the law of total probability, Bayes' theorem, and independence of events.
Offers an overview of propositional and predicate logic, sets, functions, relations, algorithms, Swiss cities, sorting tables, Covid infections, poker hands, and prime numbers.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
