MATH 356 — Honours Probability

Sample space, probability axioms, combinatorial probability. Conditional probability, Bayes' Theorem. Distribution theory with special reference to the Binomial, Poisson, and Normal distributions. Expectations, moments, moment generating functions, uni-variate transformations. Random vectors, independence, correlation, multivariate transformations. Conditional distributions, conditional expectation.Modes of stochastic convergence, laws of large numbers, Central Limit Theorem.

• Rating: 3.57 out of 5 from 399 student reviews
• Difficulty: 3.86 out of 5
• Credits: 3
• Faculty: Faculty of Science
• Department: Mathematics and Statistics
• Taught by: Louigi Addario-Berry
• Prerequisite(s): MATH 243 or MATH 255, and MATH 222 or permission of the Department.

Sections offered

• Section 001 (Lec), Tue Thu 8:35-9:55 am — 18 seats open