SYLLABUS for ST/MA 746-001 Smith Section


ST/MA 746-001
Spring 2008
Introduction to Stochastic Processes

Place ,Time,Website:
Harrelson 215 , 1:30-2:20 MWF,    WEBSITE:      http://www4.stat.ncsu.edu/~bmasmith/ST746/

Instructor:
Dr. C. E. Smith,  Cox Hall Room 513 E, 515-1907, e-mail: bmasmith@stat.ncsu.edu , office hours: Thurs  5:30-7:30  in Harrelson G100 computer lab

Teaching Assistant:
Mamiko Arai , , office hours: TBA  e-mail: marai@ncsu.edu

Prerequisites: MA 405 and MA(ST) 546 or ST 741; Linear algebra, integral and diff. calculus and a previous statistics or probability course

Text: Introduction to Stochastic Modeling, Howard Taylor & Samuel Karlin, THIRD edition, Academic Press, ISBN 0-12-684887-4, 1998.

Other reference books are on reserve in D.H. Hill Library Reserve Room under ST 746

Course Description: Markov chains and Markov processes, Poisson process, birth and death processes, queuing theory, renewal theory, stationary processes, Brownian motion. MAPLE will be used as a tool to do the linear algebra calculations of Markov chains.

Homework: Roughly weekly assignments, 10-12 total, lowest homework grade dropped. 

Some extra credit homework problems throughout the course. 

Lecture summary by student is one homework assignment. Optional project as extra credit.

Quizzes: Two one hour in class quizzes (Open Book)

Exam: Three hour exam, WED.  April 30, 1-4 pm

GRADING: Homework 25%, Quizzes 50% (25% each), Final 25%
Plus/Minus grading will be used. Exception: If you have a solid A on homework and on each of two quizzes, you will receive an A in course without taking the final.

Course Outline: cf. text
Review: Chapters 1, 2
Markov Chains: Chapters 3, 4 ,also O'Reilly chapter
Continuous time Markov Chain: Chapter 6
Poisson Process and Renewal Processes: Chapters 5, 7
Continuous Time Continuous State Processes: Chapter 8 also O'Reilly chapter
Queueing Systems: Chapter 9



LEC. TOPIC ( READINGS )
1 Introduction to Stochastic Processes, Pine Cones ( CH 1,2 )
2 Markov Chain, Defn of 1 step transion matrix ( O'Reilly chapter )
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