This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality; law of large numbers; and central limit theorem.
M. Raginsky, and I. Sason. (2012)cite arxiv:1212.4663Comment: Foundations and Trends in Communications and Information Theory, vol. 10, no 1-2, pp. 1-248, 2013. Second edition was published in October 2014. ISBN to printed book: 978-1-60198-906-2.
G. Peyré, and M. Cuturi. (2018)cite arxiv:1803.00567Comment: new version with corrected typo in Eq. 4.43 and 4.44 (minus sign in front of f, g now changed to +).