140.722.41
Probability Theory II
 Location:
 Internet
 Term:
 2nd term
 Department:
 Biostatistics
 Credits:
 3 credits
 Academic Year:
 2022  2023
 Instruction Method:
 Synchronous Online
 Class Times:

 M W, 1:30  2:50pm
 Auditors Allowed:
 No
 Undergrads Allowed:
 No
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructor:
 Contact:
 Michael Rosenblum
 Resources:
 Prerequisite:
Calculus, real analysis, 140.721
 Description:

Presents the first part of the classical results of measuretheoretic probability: random variables, distribution function, integration, types of convergence, convergence theorems, independence, BorelCantelli lemmas.
 Learning Objectives:

Upon successfully completing this course, students will be able to:
 Define a random variable and the sigmaalgebra it generates
 Integrate with respect to a probability measure
 Understand convergence of random variables, and the conditions required to prove convergence in expectation
 Assess whether two random variables are independent or not
 Define and relate the various types of convergence
 Methods of Assessment:
This course is evaluated as follows:
 75% Homework
 25% Exam(s)
 Instructor Consent:
Consent required for some students
 Consent Note:
Consent required for any students who are not in the Biostatistics PhD program
 For consent, contact:
 Special Comments:
Please note: This is the virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.