Everything can change with little or no notice at any moment…

In particular, a  lecture  can be moved to on-line mode on a very short notice, so please check your e-mail before every class.

Class number 39710

Math 505a in Fall 2025 semester: Key dates

  • August 25: first day of classes
  • September 1: Labor Day, no class
  • September 12: Last day to drop without a W AND with refund
  • October 6: Midterm Exam 1
  • October 9,10: Fall Break
  • October 10: Last day to drop without a W, BUT WITH NO refund
  • November 14: Last day to drop with a W
  • November 17: Midterm Exam 2
  • November 26-30: Thanksgiving Break
  • December 5: Final project is due; Last day of classes
  • December 17: Final exam (11am-1pm, in KAP 146)

Class schedule

Homework problems and the project

 

Instructor: Dr. Sergey Lototsky
Office: KAP 248D.
Phone: 213–740-2389.
E-mail: lototsky (at) USC (dot) edu
URL: https://dornsife.usc.edu/sergey-lototsky/
Lectures:  MWF 1-1:50pm, KAP 146
Office hours: MWF 2:15-3:15pm [in KAP 248D]

Please do not hesitate to talk to me about your problems, questions, or concerns in this class. We can always arrange a special zoom meeting.

Teaching Assistant (Grader): Inga Girshfeld
E-mail: girshfel {at} usc [dot] edu
Office hours: Tu 1-2pm, W 2-4pm, all in the Math Center (KAP 263).

Textbook: Probability and Random Processes by Geoffrey R. Grimmett and David R. Stirzaker Oxford University Press. 4th Edition (2020) is the most recent; ISBN 978–0–19–884760–1 (Hardcover) ISBN 978–0–19–884759–5 (Paperback)

Objective: To gain general knowledge and skills necessary to apply probabilistic methods to various areas of natural and social sciences.

Goal: To be ready for Math 505b (or its equivalent)

Concrete task: To be ready for a PhD-level comprehensive exam in (non-measure-theoretic) probability.

Note:  In our department (USC Mathematics), the graduate probability exam based on the material covered in MATH 505a is required for Ph.D. in Applied Mathematics  and is an option for Ph.D. in Mathematics, Masters in Applied Mathematics (both MA and MS), and Masters in Statistics.   

Save the dates! There will be two in-class one-hour exams: Monday, October 6 and Monday,  November 17, during regular lecture hours, in the regular lecture room (KAP 146). Final exam is Wednesday, December 17, 11am-1pm, in the regular lecture room.

Note: You might need a PDF Scanner, to submit your (mostly likely handwritten) work to Gradescope
in PDF format (one PDF per assignment or exam). There are many free phone apps that you can use
to scan your work to make a PDF, for instance Adobe Scan.

Homework: There will be six homeworks and a final project. You should know how to solve every
homework problem and turn in each homework on the corresponding due date. You are welcome to use
any help with all the work you do outside the classroom. During exams, you are on your own. No
calculators will be necessary (or allowed) during exams. All exams are closed book.

Please keep in mind that homework assignments are minimal requirements. To succeed in the class,
you need to solve more problems, from the book and/or from other sources. Keep all your notes,
including scratch paper, until after you are completely done with this class (or with the corresponding Graduate Exam).

Note on Use of AI
You are welcome to use  artificial intelligence (AI) powered programs as a help with homework problems, but not with  exams. While AI tools can help you brainstorm ideas or revise work you have already written, AI text generation tools may present incorrect information, biased responses, and incomplete analyses. To adhere to our university values, you must cite any AI-generated material (such as text or images) included or referenced in your work and provide the prompts used to generate the content.  I will not be using any AI tools in grading your work.

Grading:

  • Homeworks 20% total
  • Two One-Hour Exams, 40% total (20% each)
  • Final Project 10%
  • Final Exam 30%

To put is differently: you get 70% of the final grade from in-class work (two midterms and the final
exam) and 30% of the final grade from homeworks and the project.

List of topics to be learned    More detailed version with references

Previous Graduate Exams on the topic of the class from the USC Math Department:

1999-2011   2012-2025   505aFall2025

Some ideas for some of the solutions

Other materials