Math 280 Home Page (Driver, F2018-S2019)

 

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Math 280 -- Probability Theory (Fall 2018 - Spring 2019) Course Information

(http://www.math.ucsd.edu/~bdriver/280_18-19_prob/index.htm)


  •  New due date for Homework #7 -- one week later. Two problems have been added to the assignment though.
  •   Exercise 2.46 on Homework 6 has been moved to a "look at" problem.
  • Please postpone 10.17 of Resnick until the homework #3.
  • Homework problems are due at the start of class on Wednesday's this quarter.
  •   Please find the lecture note problems in the Lecture notes for more context and possible assumptions for the problem which do not appear in the stand-alone problems on this web-page.
  •   There is one Monday holidays this quarter: Monday, May 27 (Memorial Day).

Instructor:       Bruce Driver, APM 5260, 534-2648
Office Hours:   M. & F. 10am-11am


Course TA :   
Nantawat Udomchatpitak (nudomcha@ucsd.edu) AP&M 5748
Office Hours:  
Monday 1-3pm in APM5478

Meeting times: MWF 9:00 -- 9:50 AM in AP&M 5402.

Lecture Notes :   I will be following these notes throughout the year.

Recommended Textbook:  Resnick, S. A Probability Path, Birkhauser, 2005ed. UCSD students may access this book electronically (when on campus) at:

https://link.springer.com/book/10.1007%2F978-0-8176-8409-9


Homework:   There will be weekly homework assignments due at the start of each Monday Class.  No late homeworks will be accepted.

Grades:   Based on homework scores.  The last homework assignment should be done without consultation with other students.

You should also routinely login to your TED (https://ted.ucsd.edu/) account for more course information.

Description: Math 280ABC is the fundamental graduate probability sequence. It covers measure theoretic probability essential for the pursuit of research in probability or in fields in which probability is used in applications. Topics to be covered include:

  1. Measure and integration from a probabilistic perspective.

  2. Basic probabilistic notions of random variables, expectation, independence.

  3. Limit theorems: laws of large numbers, convergence in distribution, central limit theorems.

  4. Martingale theory: conditional expectation, convergence theorems, optional stopping.

  5. Stochastic processes: a selection from random walk, Markov chains, Brownian motion, Markov processes, statistical mechanics, stable processes, stochastic integration.

Topics 1, 2, and parts of 3 will be covered in Math 280A. The remainder of topic 3, and topics 4 and 5 will be covered in the subsequent two quarters of Math 280B, C. The text below will be supplemented with class lecture notes.


More on line reference books: Here are some more probability books you can access on-line (when on campus at UCSD)


 

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Last modified on Monday, 26 November 2018 10:39 AM.