Description

Prereq: Calculus II (GIR). Introduction to probability theory. Probability spaces and measures. Discrete and continuous random variables. Conditioning and independence. Multivariate normal distribution. Abstract integration, expectation, and related convergence results. Moment generating and characteristic functions. Bernoulli and Poisson process. Finite-state Markov chains. Convergence notions and their relations. Limit theorems. Familiarity with elementary probability and real analysis is desirable. Final examination.

Credits

12

Recent Professors

Schedule Planner

Recent Semesters

Fall 2019

Offered

MW, F

Avg. Sections

3