MTH 202 - Intro to Stochastic Processes


MTH 202 Intro to Stochastic Processes Spring 2026

Instructor Information

Arjun Krishnan

  • Please call me Arjun or Professor Arjun
  • Office: Hylan 817
  • Office Hours: Fridays 1.30pm - 3.00pm Hylan 817
  • Email:

TA

Hari Nathan

  • Office Hours: Thursday 3-4pm in the Hylan 711.

Course Details

Lecture details

MW 9AM - 10:15AM Morey 501

Prerequisites

MTH 201

Description

The official course description is

Theory and applications of random processes including Markov chains, Poisson processes, birth-and-death processes, and random walks.

Course Objectives

MTH 202 is the sequel to MTH 201, Intro to Probability. In 201, we studied the basics of probability theory like random variables and probability distributions. In this course, we will study random variables that have an additional time parameter; i.e., a stochastic process. We will primarily study a canonical discrete-time stochastic process called a Markov chain. Markov chains appear in many fields of science like physics, biology and economics. The theory will be supplemented by examples from these fields. Some examples of Markov chains and processes that we will study include Poisson processes, birth-and-death processes, random walks and queues.

Time permitting, we will briefly touch upon the theory of martingales and Brownian motion. The course will not be mathematically rigorous, but we will give short proofs whenever they’re illuminating.

Course Learning Outcomes

  • Understand the basics of discrete-time stochastic processes.
  • Analyze the behavior of Markov chain models.
  • Construct simple Markov chain models with real-world applications.

Objectives

Grading

Homework 30%
Quizzes 40%
Final 30%

Here is the grade distribution from the last time I taught it.

Grade Percentage
A 37.5
B 50
C 12.5

Guaranteed grades: if you make these scores, then you are guaranteed a letter grade in the following ranges.

Grade Cutoff
A 90
B 80
C 70

I sometimes “curve up” linearly to help students with lower scores.

Textbook

Introduction to Stochastic Modeling, Karlin and Pinsky. You can get an older edition, and its essentially the same: Karlin and Taylor. You can also buy them second hand.

I do not recommend getting a pirated copy from one of those dodgy internet sites like Anna’s archive, z-library or libgen. There are a few copies on reserve at Carlson Library.

This will be supplemented by material from the following books. Pdfs of whatever you need will be posted online.

Schedule

More information can be found on the schedule

Homework

More information on the homework page.

Exams

More information on the exam page.

Academic Honesty

All assignments and activities associated with this course must be performed in accordance with the University of Rochester’s Academic Honesty Policy.

You may work together on homework, but copying on homework or exams is NOT allowed, and it will be considered academic dishonesty.

Any usage whatsoever of online solution sets or paid online resources (chegg.com, chatGPT or similar) is considered an academic honesty violation and will be reported to the Board on Academic Honesty. In particular, any assignment found to contain content which originated from such sources is subject to a minimum penalty of zero on the assignment and a full letter grade reduction at the end of the semester (e.g. a B would be reduced to a C). This applies even if the unauthorized content was obtained through indirect means (through a friend for instance) and/or the student is seemingly unaware that the content originated from such sources. If you have any questions about whether resources are acceptable, please check with your instructor.

Additional Help

Work with your classmates (but don’t copy assignments). It is essential to not fall behind because each lecture is based on previous work. If you are having any difficulties, seek help immediately. There are several avenues for you to get help and ask questions, outside of lecture:

Disability Support

The University of Rochester respects and welcomes students of all backgrounds and abilities. In the event you encounter any barrier(s) to full participation in this course due to the impact of a disability, please contact the Office of Disability Resources. The access coordinators in the Office of Disability Resources can meet with you to discuss the barriers you are experiencing and explain the eligibility process for establishing academic accommodations.

Office of Disability Resources (disability@rochester.edu; (585)275-9049; 1-154 Dewey Hall)

To be granted alternate testing accommodations, you (the student) must fill out forms with the Office of Disability Resources at least seven days before each and every exam. These forms are not sent “automatically.” Professors are not responsible for requesting alternative testing accommodations at the Office of Disability Resources, and they are not obligated to make any accommodations on their own.