Probability Theory & Stochastic Analysis (450-1-71)

Instructors

Reza Gheissari

Meeting Info

Lunt Hall 102: Mon, Wed, Fri 1:00PM - 1:50PM

Overview of class

Probability spaces, random variables and expectations, independence, conditional expectations and probabilities, the Kolmogorov existence theorem. The law of large numbers and random series: the weak and strong law of large numbers, convergence of random series, 0-1 laws, the law of the Internet logarithm. Limited distributions and the central limit problem: weak convergence of measures, characteristic functions, the central limit theorem, stable distributions, limit distributions for sums and maxima, infinitely divisible distributions, recurrence.

Class Materials (Required)

978-1108473682
Probability: Theory and Examples, 5th edition
Author: Durrett
Publisher: Cambridge

Class Materials (Suggested)

No suggested materials. See required materials

Enrollment Requirements

Enrollment Requirements: Preregistration in this course is reserved for students who are majoring in Mathematics.