STA 624 Applied Stochastic Processes

This is a course on stochastic processes, which involve collections of random variables indexed by time or by space. In this course you will learn the nomenclature and techniques needed for understanding the major types of stochastic processes, how to apply these processes in mathematical modeling, and how to effectively compute and simulate using these processes. We will cover materials including (not limited to) discrete-time and continurous-time Markov Chain, Reversible Markov Chain, hidden Markov Model (HMM) (see more details at a sylabus).

Spring Semester 2014


Introduction to Stochastic Processes 2nd edit G. F. Lawler.


Ruriko Yoshida, Associate Professor of Statistics

Time and Place for STA624, Spring Semester 2014

  • Tue and Thurs 11:00 AM - 12:15 PM, 335 MDS

Course Website

Syllabus For STA 624

We will cover Chapter 1, 2, 3, and 5. In addition, We will cover Hidden Markov Model and also applications to computational Biology (especially, to alignment problems and also evolutional model). For more details see PDF.


  • Exam 1 Thurs March 6th.
  • Exam 2 Thurs April 24th.
  • Final Tuesday May 6th at 10:30AM to 12:30PM.


There will be two in-class exams, graded homeworks, programming assignments, and a final exam: these will count 40%, 20%, 15%, and 25% of your grade, respectively.

Students with excused absences will be given a make-up exam. No homework will be made up for credit, but it's important to make it up for your own benefit. The lowest scored HW will be discarded. Late homework will not be accepted. No make up final.

STA 624 Handout



Write each problem neatly. If you have any question about grading, you must prove why you think so. Regrading will be in 7 days after returning. After 7 days, regrading will NOT be accepted. All exams will be in class. Calculator is allowed. They are closed book exams.

Homework for STA 624, Spring Semester 2014