Introduction to Probability

Catalog description

Discrete and continuous probability spaces, axiomatic formulation, combinatorics, conditional probability and independence, standard discrete and continuous probability distributions (including uniform, Bernoulli, binomial, Poisson, geometric, normal, and exponential), random variables, expectation and variance, joint distributions, and limit theorems. Emphasis on modeling. Simple proofs required. Additional topics may include random walks, branching processes, and generating functions. May not be taken for credit by students who received credit for: MATH 440 . Enrollment Requirement(s): for graduate students MATH 260 with a grade of C (2.0) or better. Prerequisite(s): for undergraduates MATH 260 with a grade of C (2.0) or better.