Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Delves into advanced probability theory, covering inequalities, trials, distributions, and calculations for probabilities and expectations.
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
