STAT2702 Probability

This topic examines: the set-theoretic formulation of events and Kolmogorov's axioms of probability; counting techniques; conditional probability and independence; discrete distributions, including binomial, geometric, negative binomial, hypergeometric and Poisson; continuous distributions, including uniform, exponential, gamma, normal and Cauchy; expectation, mean and variance; probability and moment generating functions; several random variables; correlation; bivariate distributions, including trinomial and bivariate normal distributions; the mean and variance of a random sample; limit theorems, including the central limit theorem.

This topic aims to introduce students to the mathematical development and applications of elementary probability theory.

1. Have acquired an understanding of the conceptual foundations of elementary probability theory
2. Understand mathematical arguments and proofs relevant to elementary probability theory
3. Understand standard families of discrete and continuous probability distributions
4. Solve applied problems requiring the techniques of elementary probability theory and the standard families of discrete and continuous probability distributions