Instructor: Tim Chumley
Office: Clapp 404b
Phone: 5382299
email: tchumley
Office Hours: tentatively Mondays 10:00–11:00, Tuesdays 4:00–5:00, Wednesdays 3:00–4:00, Thursdays 9:00–10:00, and by appointment
Textbook: Introduction to Stochastic Processes with R by Robert P. Dobrow, ISBN: 9781118740651;
on library reserve under QC20.7.S8 D63 2016;
available as a free etext
Announcements will be posted here throughout the semester.
Feb 3: Some clarifying remarks about rewrites have been posted below in the Homework section.
Feb 2: Here is another modeling competition opportunity taking place at Amherst College April 21 called SCUDEM (in addition to the one I wrote to you about taking place next week).
Check the syllabus for all the important class policies (grades, attendance, etc.).
There will be weekly homework assignments throughout the semester to be turned in, as well as suggested problems to be considered as additional practice.
Assignment  Due 

Problem set 0 (solutions)  Jan 29 
Problem set 1 (solutions)  Feb 2 
Problem set 2 (solutions)  Feb 9 
Problem set 3  Feb 16 
Problem set 4  Feb 23 
There will be three exams. The dates for the two midterms are subject to change slightly:
Exam  Date  Time and Location  Material  Study material  Solutions 

Exam 1  Mar 2  in class, takehome  
Exam 2  Apr 6  in class, takehome  
Final exam  May 3  7  selfscheduled 
Our plan is to cover the textbook chapters 1 – 3, and parts of 4 – 7. Below is a rough outline of what is to be covered week by week through the semester. Please check back regularly for precise details on what is covered, as well as postings of inclass worksheets and other activities. Also note that the days of the week under Sections in the table below provide links to class notes.
Week  Sections  Inclass activities  Problems 

Jan 22  Jan 26  Wednesday 1.1, 1.2, 2.1 Friday: 2.2 
First day info, State spaces, index sets Markov transition matrix, graphs 
1.1, 1.2, 1.3, 1.4, 1.9, 1.35 2.8, 2.9, 2.10 
Jan 29  Feb 2  Monday: 2.3, 2.4 Wednesday: 2.3 Friday: 2.5 
nstep distribution (solutions) Simulation, RMarkdown More simulation 
2.1, 2.2, 2.6, 2.25, 2.26 2.4, 2.5, 2.11, 2.17 2.23, 2.24, 2.27 
Feb 5  Feb 9  Monday: 3.1, 3.2 Wednesday: snow day Friday: 3.2, 3.3 
Stationary distribution Communication classes 
2.18, 3.1, 3.2, 3.5, 3.8, 3.10 3.13, 3.14a, 3.63 
Feb 12  Feb 16  Monday: 3.3 Wednesday: 3.3 Friday: 3.4 
Canonical decomposition Excursions 
3.28, 3.29 3.17, 3.22 3.14, 3.18, 3.34 
Feb 19  Feb 23  Monday: 3.5 Wednesday: 3.6, 3.8 Friday: 3.8 
Ergodic chains 

Feb 26  Mar 2  4.1, review  
Mar 5  Mar 9  4.2 – 4.4  
Mar 12  Mar 16  spring break  
Mar 19  Mar 23  5.1, 5.2  
Mar 26  Mar 30  6.1, 6.2  
Apr 2  Apr 6  6.4, 6.5  
Apr 9  Apr 13  7.1, 7.2  
Apr 16  Apr 20  7.3, 7.4  
Apr 23  Apr 27  TBA  
Apr 30  May 4  review 
We’ll devote the last week of the semester to a minisymposium of short group presentations. Since the field of stochastic processes is rich with interesting examples and topics, more than we could cover in a single semester, each group of 23 students will choose a topic/application that we might otherwise not have time for in class. We’ll also plan to have a writing component to the project and some preliminary deliverables in the lead up to the final week. More details will be discussed in class later in the semester.
Here’s a few ways to get help:
Everyone is invited to join DataCamp, which provides an introductory R tutorial. It’s a convenient way to gain some familiarity with R, a useful tool for our course and beyond. Our textbook also provides a thorough tutorial of some R basics in the appendix.
Our textbook also has a useful collection of R scripts available here; contained there are all the R code snippets you’ll notice interspersed in the text.