The study of probabilistic and inferential tools is important for applications in data science. Topics covered: Probability distributions; decision theory, Bayesian inference, classification, prediction; law of large numbers, central limit theorem; point and interval estimation; multiple testing, false-discovery rates. Syllabus (2021 Fall).pdf
