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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 finite probability spaces, random permutations, graphs, and trees with examples and calculations.
Covers the basics of probability theory, including definitions, calculations, and important concepts for statistical inference and machine learning.
Explores the Monty Hall problem, discussing optimal strategies and challenging intuition.
Covers the concept of convergence in distribution for random variables and its significance in probability theory.
Explores the generalization of Martingale Central Limit Theorem to sub- and supermartingales, discussing key properties and corollaries.
