Name | Role | Office | Office hours | |
Yuriy Nemish | Instructor | - | ynemish@ucsd.edu |
|
Toni Gui | Teaching Assistant | - | ttgui@ucsd.edu |
|
Alec Todd | Teaching Assistant | - | altodd@ucsd.edu |
|
Date | |||
Lecture A00/B00 (Nemish) | Monday, Wednesday, Friday | - | - |
Date | Time | Link | |
Q&A A00 (Nemish) | Monday, Wednesday, Friday | 1:00pm - 1:25pm | Zoom |
Q&A B00 (Nemish) | Monday, Wednesday, Friday | 4:00pm - 4:25pm | Zoom |
Discussion A01 (Gui) | Monday | 7:00pm - 7:50pm | Zoom |
Discussion A02 (Gui) | Monday | 6:00pm - 6:50pm | Zoom |
Discussion B01 (Todd) | Monday | 7:00pm - 7:50pm | Zoom |
Discussion B02 (Todd) | Monday | 6:00pm - 6:50pm | Zoom |
First Midterm Exam A00 | Wednesday, Apr 22 | 1:00pm - 1:50pm | ?? |
First Midterm Exam B00 | Wednesday, Apr 22 | 4:00pm - 4:50pm | ?? |
Second Midterm Exam A00 | Wednesday, May 20 | 1:00pm - 1:50pm | ?? |
Second Midterm Exam B00 | Wednesday, May 20 | 4:00pm - 4:50pm | ?? |
Final Exam A00 | Thursday, Jun 11 | 11:30am - 2:29pm | ??? |
Final Exam B00 | Thursday, Jun 11 | 3:00pm - 5:59pm | ??? |
Welcome to Math 180C: a one quarter course introduction to stochastic processes (II). According to the UC San Diego Course Catalog, the topics covered are Markov chains in discrete and continuous time, random walk, recurrent events and other topics.
Here is a more detailed listing of course topics, in the sequence they will be covered, together with the relevant section(s) of the textbook. While each topic corresponds to approximately one lecture, there will be some give and take here.
Q&A | Week | Topic | PK | Slides | Video | ||
---|---|---|---|---|---|---|---|
03/30 | 1 | Administrivia | - | - | - | ||
04/01 | 1 | Birth processes | 6.1 | Slides 1 | Video 1 | ||
04/03 | 1 | Birth and death processes | 6.2 - 6.3 | Slides 2 | Video 2 | ||
04/06 | 2 | Birth and death processes | 6.2 - 6.3 | ||||
04/08 | 2 | Hitting probabilities | 6.5 | Slides 3 | Video 3 | ||
04/10 | 2 | General continuous-time Markov chains | 6.6 | Slides 4 | Video 4 | ||
04/13 | 3 | General continuous-time Markov chains | 6.6 | ||||
04/15 | 3 | Kolmogorov's forward and backward equations | 6.3, 6.6 | Slides 5 | Video 5 | ||
04/17 | 3 | Kolmogorov's forward and backward equations | 6.3, 6.6 | ||||
04/20 | 3 | Stationary distributions and long-run behavior | 6.4 | Slides 6 | Video 6 | ||
04/22 | 3 | Stationary distributions and long-run behavior | 6.4 | ||||
04/24 | 4 | Midterm 1 | - | - | |||
04/27 | 5 | Conditioning on a continuous random variable | 2.4 | Slides 7 | Video 7 | ||
04/29 | 5 | Introduction to renewal processes | 7.1 | Slides 8 | Video 8 | ||
05/01 | 5 | Introduction to renewal processes | 7.1 | ||||
05/04 | 6 | Examples of renewal processes | 7.2 - 7.3 | Slides 9 | Video 9 | ||
05/06 | 6 | Examples of renewal processes | 7.2 - 7.3 | ||||
05/08 | 6 | Asymptotic results for renewal processes | 7.4 | Slides 10 | Video 10 | ||
05/11 | 7 | Asymptotic results for renewal processes | 7.4 | ||||
05/13 | 7 | Generalizations of renewal processes | 7.5 | Slides 11 | Video 11 | ||
05/15 | 7 | Generalizations of renewal processes | 7.5 | ||||
05/18 | 8 | Martingales | 2.5 | Slides 12 | Video 12 | ||
05/20 | 8 | Midterm 2 | - | - | |||
05/22 | 8 | Martingales | 2.5 | ||||
05/25 | 9 | Memorial Day | |||||
05/27 | 9 | Definition and basic properties of Brownian motion | 8.1 | Slides 13 | Video 13 | ||
05/29 | 9 | The reflection principle | 8.2 | Slides 14 | Video 14 | ||
06/01 | 10 | Processes derived from Brownian motion | 8.3-8.4 | Slides 15 | Video 15 | ||
06/03 | 10 | Processes derived from Brownian motion | 8.3-8.4 | ||||
06/05 | 10 | Review | - |
Prerequisite: MATH 180B or concent of instructor.
Lecture: You are responsible for material presented in the lecture whether or not it is discussed in the textbook. You should expect questions on the exams that will test your understanding of concepts discussed in the lecture.
Homework: Homework assignments are posted below, and will be due at 11:59pm on the indicated due date. You must turn in your homework through Gradescope; if you have produced it on paper, you can scan it or simply take clear photos of it to upload. Your lowest homework score will be dropped. It is allowed and even encouraged to discuss homework problems with your classmates and your instructor and TA, but your final write up of your homework solutions must be your own work.
Midterm Exams: The two midterm exams will take place during the lecture time at the dates listed above.
Final Exam: The final examination will be held at the date and time stated above.
Administrative Links: Here are two links regarding UC San Diego policies on exams:
Regrade Policy:
Grading: Your cumulative average will be the best of the following three weighted averages:
Your course grade will be determined by your cumulative average at the end of the quarter, and will be based on the following scale:
A+ | A | A- | B+ | B | B- | C+ | C | C- |
97 | 93 | 90 | 87 | 83 | 80 | 77 | 73 | 70 |
The above scale is guaranteed: for example, if your cumulative average is 80, your final grade will be at least B-. However, your instructor may adjust the above scale to be more generous.
Academic Integrity: UC San Diego's code of academic integrity outlines the expected academic honesty of all studentd and faculty, and details the consequences for academic dishonesty. The main issues are cheating and plagiarism, of course, for which we have a zero-tolerance policy. (Penalties for these offenses always include assignment of a failing grade in the course, and usually involve an administrative penalty, such as suspension or expulsion, as well.) However, academic integrity also includes things like giving credit where credit is due (listing your collaborators on homework assignments, noting books or papers containing information you used in solutions, etc.), and treating your peers respectfully in class. In addition, here are a few of our expectations for etiquette in and out of class.
Weekly homework assignments are posted here. Homework is due by 11:59pm on the posted date, through Gradescope. Late homework will not be accepted.