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 measure-theoretic probability: random variables, distribution function, integration, types of convergence, convergence theorems, independence, Borel-Cantelli lemmas.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Define a random variable and the sigma-algebra 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.