Spring 2017: MTH 202

Instructor:

Grader:

Textbook

Lecture notes in PDF format will be provided by the instructor on a weekly basis. The main textbook to follow, at least initially, is

Sheldon M. Ross, ``Introduction to Probability Models,’’ Elsevier, U.S., U.K., 2010.

Supplementary textbooks of relevance are

Gregory F. Lawler, ``Introduction to Stochastic Processes,’’ Taylor & Francis Group, U.S.A., 2006.

Bernt Oksendal, ``Stochastic Differential Equations, An Introduction with Applications,’’ Springer-Verlag, Berlin, Heidelberg, New York, 2003.

Prerequisites

Math 201 and Math 165

Course description

Overview

This course deals with stochastic processes. Discussion will not be completely rigorous, but explanations will be intended to be complete.

Possible topics to be covered include reviews (probability theory, random variables, conditional probability and conditional expectation), Markov chains, exponential distribution and the Poisson processes, continuous-time Markov chains, renewal theory and its applications, Brownian motion and Ito’s calculus.

Grades

5 percent for quizzes, 25 percent for homework, 30 percent for mid-term Exam, 40 percent for final Exam.

When the quizzes will be given in class, the instructor will E-mail students at least a day in advance, and the lowest quiz score will be dropped.

Any student with 90 percent or higher will get at least A-, any student with 80 percent or higher will get at least B-, any student with 70 percent or higher will get at least C-. Besides, the instructor’s discretion will be utilized if necessary.