This course focuses on probability theory, with the view of probability distributors as models for phenomena with statistical regularity. 1. Discrete distributions (binomial, hypergeometric, and Poisson); 2. Continuous distributions (normal, exponential) and densities; 3. Random variables, expectation, independence, conditional probability; 4. Introduction to the law of large numbers and the central limit theorem; 5. Sampling distributions; 6. Elementary statistical inference (confidence intervals and hypothesis tests).
MH1800 and MH1801