STAT 475 - Introduction to Stochastic Processes

Units: 3
Theory of stochastic models with applications to science and engineering. Poisson processes. Markov processes. Elementary birth-death processes, queues. Limit theorems. Computer simulation. Applications: e.g., reliability, epidemiology, Bayesian MCMC.

Prerequisites: STAT 320 or STAT 316.
Possible Instructional Methods: On-ground.
Grading: A-F or CR/NC (student choice).
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Demonstrate the use of probability models with dependent random variables.
Apply probability models to real data examples
Write script to simulate stochastic processes.