STAT 5378 -- Stochastic Processes -- Fall 2016


Instructor

Dr. Alex Trindade, 228 Mathematics & Statistics Building.
E-mail: alex.trindade"at"ttu.edu.
Course Meets: 3:30 - 4:50 TR in MATH 115.
Office Hours: Tue/Wed/Thurs 12:00-1:00, or by appointment.

Text Books

Course Objectives and Syllabus

This is a second course in Probability, studying the mathematically basic kinds of random process, intended for majors in Statistics and related quantitative fields. The prerequisite for the course is STAT 5328. Chapters to be covered are as follows:

Expected Student Learning Outcomes

The heart of the course will consist of chapters 3-5 of the text, concentrating on the following major topics: Markov chains; transition probabilities; the random walk; branching processes; classification of the states of a Markov chain; Poisson processes. By the end of the course the student should have a good grasp of concepts, theory and methodology concerned with the modeling of stochastic processes, and their application in various fields.

Methods of Assessing the Expected Learning Outcomes

The expected learning outcomes for the course will be assessed through a mix of homework assignments and tests. The course grade will be determined from homework problem sets (20%), two midterm tests (25% each), and a comprehensive final exam (30%). Grades will be posted on raiderlink. The traditional grading scale will be used: The test schedule is as follows:

Homework Problem Sets

There will be weekly problem sets due on thursdays. All work handed in must be stapled together. No late submissions will be accepted. Only a subset of the hwk may be graded; if your hwk omits the problem(s) chosen to be graded your grade will be zero. Start each problem on a new page. Only otherwise stated, these are the "Problems" in the text.

Policies


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