Stat 150: Stochastic Processes (Fall 2022)

Course information

Instructor: Benson Au
Lectures: MWF 2:10p-3:00p (Cory 277)
Office hours: MF 3:00p-4:00p (Evans 355)

GSI: Adam Quinn Jaffe
Discussion section (optional): Tu 1:10p-2:00p (Evans 334)
Office hours: Tu

Textbooks:

An Introduction to Stochastic Modeling by Pinsky and Karlin (freely available through the university library here)
Essentials of Stochastic Processes by Durrett (freely available through the university library here)

To reiterate, the textbooks are freely available through the university. Note that you must be connected to the university Wi-Fi or VPN to access the ebooks from the library links. Furthermore, the library links take some time to populate, so do not be alarmed if the webpage looks bare for a few seconds.

Exam schedule

Please bring your student ID to the exams.

Midterm #1: TBD

Midterm #2: TBD

Final: Thursday, 15 Dec, 3:00p-6:00p in TBD

Homework assignments

PK refers to Pinksy and Karlin. D refers to Durrett. Note that there are both exercises and problems in PK. Make sure you are doing the correct assignment.

Homework 0, due August 29th at 11:59 PM on Gradescope.

Homework 1 (.tex), due September 2nd at 11:59 PM on Gradescope.

Homework 2, (.tex), due September 16th at 11:59 PM on Gradescope.

Homework 3, (.tex), due September 23rd at 11:59 PM on Gradescope.

Homework 4, (.tex), due September 28th at 11:59 PM on Gradescope.

Homework 5, (.tex), due October 7th at 11:59 PM on Gradescope.

Homework 6, (.tex), due October 14th at 11:59 PM on Gradescope.

Homework 7, (.tex), due October 28th at 11:59 PM on Gradescope.

Homework 8, (.tex), due October 31st at 11:59 PM on Gradescope.

Homework 9, (.tex), due November 28th at 11:59 PM on Gradescope.

Homework 10, (.tex), not due.

Course Calendar

The following calendar is subject to revision during the term. The section references are only a guide: our pace may vary from it somewhat. PK refers to Pinksy and Karlin. D refers to Durrett.

Week 1, Aug 24: Probability review (D A.1-A.3, PK 1.1-1.6), Conditional probability and conditional expectation (PK 2.1)

Week 1, Aug 26: Conditional probability and conditional expectation (PK 2.1), Random sums (PK 2.3)

Week 2, Aug 29: Random sums (PK 2.3), Markov chains (PK 3.1, D 1.1)

Week 2, Aug 31: Markov chains (PK 3.1-3.2, D 1.1-1.2)

Week 2, Sep 2: Markov chains (PK 3.4, 3.7)

Week 3, Sep 5: Labor day

Week 3, Sep 7: Markov chains (PK 3.4, 3.7)

Week 3, Sep 9: Gambler's ruin and branching processes (PK 3.6, 3.8, 3.9)

Week 4, Sep 12: Branching processes (PK 3.8, 3.9)

Week 4, Sep 14: Long-run behavior of Markov chains (PK 4.1)

Week 4, Sep 16: Long-run behavior of Markov chains (PK 4.2)

Week 5, Sep 19: Long-run behavior of Markov chains (PK 4.2, 4.3)

Week 5, Sep 21: Long-run behavior of Markov chains (PK 4.3, 4.4)

Week 5, Sep 23: Long-run behavior of Markov chains (PK 4.4)

Week 6, Sep 26: Poisson process (PK 5.1, D 2.1)

Week 6, Sep 28: Poisson process (PK 5.2, D 2.2)

Week 6, Sep 30: Midterm 1

Week 7, Oct 3: Poisson process (PK 5.2, 5.3, D 2.2)

Week 7, Oct 5: Poisson process (PK 5.3, 5.4, D 2.2)

Week 7, Oct 7: Poisson process (PK 5.3, 5.4)

Week 8, Oct 10: Poisson process (PK 5.4)

Week 8, Oct 12: Poisson process (PK 5.4, D 2.3, 2.4)

Week 8, Oct 14: Renewal process (D 2.3, PK 7.1)

Week 9, Oct 17: Renewal process (PK 7.1-7.3)

Week 9, Oct 19: Renewal process (D 3.1, PK 7.5)

Week 9, Oct 21: Renewal process (D 3.1, 3.2, PK 7.5)

Week 10, Oct 24: Renewal process (D 3.2.1, 3.2.3)

Week 10, Oct 26: Renewal process (D 3.3.2)

Week 10, Oct 28: Continuous-time Markov chains (D 4.1)

Week 11, Oct 31: Continuous-time Markov chains (D 4.1)

Week 11, Nov 2: Midterm 2

Week 11, Nov 4: Continuous-time Markov chains (D 4.2)

Week 12, Nov 7: Continuous-time Markov chains (D 4.2)

Week 12, Nov 9: Continuous-time Markov chains (D 4.3)

Week 12, Nov 11: Veterans Day

Week 13, Nov 14: Continuous-time Markov chains (D 4.3)

Week 13, Nov 16: Continuous-time Markov chains (D 4.4)

Week 13, Nov 18: Continuous-time Markov chains (D 4.4), Martingales (D 5.1)

Week 14, Nov 21: Martingales (D 5.1, 5.2)

Week 14, Nov 23: Non-Instructional Day

Week 14, Nov 25: Thanksgiving

Week 15, Nov 28: Martingales (D 5.2, 5.3)

Week 15, Nov 30: Martingales (D 5.3, 5.4)

Week 15, Dec 2: Martingales (D 5.4)

Week 16, Dec 5: RRR week

Week 16, Dec 7: RRR week

Week 16, Dec 9: RRR week

Week 17, Dec 15: Final exam