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Overview

Mathematics & Statistics (Sci) : 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.

Terms: Fall 2017

Instructors: Chen, Linan (Fall)

• Fall

• Prerequisite(s): MATH 133 or MATH 134, and MATH 222 or permisson of the Department.

• Corequisite(s): MATH 242 or MATH 254