Instructor: Tim Chumley
Office: Clapp 423
Phone: 413-538-2525
e-mail: tchumley
Office Hours: Mondays & Wednesdays 1:00-2:00; Tuesdays & Thursdays 2:00-3:00; additional availability 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 e-text

## Announcements

Announcements will be posted on the Course Announcements Moodle forum throughout the semester, but essentially all other materials will be posted on this page.

## Syllabus

Check the syllabus for all the important class policies (grades, attendance, etc.).

## Homework

There will be weekly homework assignments throughout the semester to be turned in. Please read these guidelines for writing in our class.

• General information. A selection of problems will be assigned to be written up individually and turned in each week.
• These problems will be due Fridays at 5 pm.
• You may work with others but the writing should be done on your own.
• You should be enrolled automatically. Please let me know if you have any issues logging in.
• Collaboration. I want you to work together on the homework! The process of explaining your ideas to one another really helps in learning math. However, you must write up the assignments on your own and avoid copying others’ work directly. Also, please only write what you understand so that I know where to help, and please avoid using online forums like Math StackExchange, solutions manuals, or similar resources. A huge part of learning in this class comes from figuring out how to get unstuck by spending time thinking on your own or talking to me and classmates; these other resources can end up being counter-productive in the long term.
• Rewrites. Homework is for practice, and you are not expected to write perfect answers from the start!
• You will be allowed to submit revisions of most problems for full credit each week.
• Your revisions will be due on Fridays at 5 pm.
Assignment Due
Homework 0 Jan 28
Homework 1 Feb 4
Homework 2 Feb 11
Homework 3 Feb 18
Homework 4 Feb 25
Homework 5 Mar 11
Homework 6 Mar 25
Homework 7 Apr 1
Homework 8 Apr 8
Homework 9 Apr 22
Homework 10 Apr 29

## Exams

There will be two midterm exams. The dates for the exams are subject to change slightly.

Exam Date Format Material
Exam 1 Mar 3 TBA TBA
Exam 2 Apr 14 TBA TBA

## Project

In lieu of a final exam, we’ll devote the last week of the semester to a mini-symposium 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 2-3 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.

## Course plan

Our plan is to cover most of chapters 1-3 and 6-7 in the textbook, and possibly some of 4, 5, or 8, time permitting. 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 class materials like lecture notes.

#### Introduction

##### Thursday
• Topic: Sections 2.1, 2.3: $$n$$-step transitions.
• Class materials: Lecture notes
• After class:

#### Chapter 2

##### Tuesday
• Topic: Sections 2.2, 2.3, 2.4: Random walks.
• Class materials: Lecture notes
• After class:
##### Thursday
• Topic: Sections 2.2, 2.3, 2.5: Joint distributions.
• Class materials: Lecture notes
• After class:

#### Chapter 3

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 3

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 3

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### TBA

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 6

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Spring Break

##### Tuesday
• Topic: Spring break, no class.
##### Thursday
• Topic: Spring break, no class.

#### Chapter 6

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 7

##### Tuesday
• Topic: Community day, no class.
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 7

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Chapter 7

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### TBA

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Presentations

##### Tuesday
• Topic:
• Class materials:
• After class:
##### Thursday
• Topic:
• Class materials:
• After class:

#### Wrap up

##### Tuesday
• Topic: Wrap up.
• Class materials:
• After class: Enjoy your summer! Keep in touch!

## Getting help

Here are a few ways to get help:

• Office Hours: Mondays & Wednesdays 1:00-2:00; Tuesdays & Thursdays 2:00-3:00; additional availability by appointment
• Study groups: Other students in the class are a wonderful resource. I want our class to feel like a community of people working together. Please get in touch if you’d like me to help you find study partners, and please reach out if you’d like others to join your group. You may work together on homework, explain and check answers, but make sure you write what you know on homework in order to get good feedback.

## Resources

• 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; contained there are all the R code snippets you’ll notice interspersed in the text.
• I’ve collected some resources to help you with some basics of RMarkdown.
• Here is a RMarkdown/LaTeX template file for writing nicely formatted documents, along with its pdf output.
• A LaTeX quick reference is available for commonly used symbols.
• RStudio Server is a cloud service that lets you edit and compile R and RMarkdown files through a web browser so that no local installation is needed. The server is hosted on the MHC network and you need to be on the VPN to access it if you’re away from campus.
• You can also install R and RStudio locally on your personal computer (you must install R before RStudio), or you can also use RStudio Cloud, which is a commercial RStudio cloud service with a free tier.