Course Description
Central limit theorems, random walks, Markov chains and processes, Brownian motion, branching and renewal processes, diffusion processes and queueing processes and applications.
Additional Requirements for Graduate Students:
Additional theoretical problems will be assigned to graduate students.
Athena Title
INTR PROBABILITY II
Equivalent Courses
Not open to students with credit in STAT 8170
Prerequisite
STAT 4710/6710
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
This course continues the non-measure-theoretic introduction to probability offered by STAT 4/6710 and proceeds into the area of stochastic processes. Students are introduced to the basic ideas of stochastic processes and study the most commonly used classes of processes in applications. Students will learn the theory of stochastic processes and will gain an understanding of their usefulness both as direct models of real-world phenomena and as components of statistical modeling and theory.
Topical Outline
Central limit theorems, random walks, Markov chains and processes, Brownian motion, branching and renewal processes, diffusion processes, queuing processes, and applications.