140.723.01
Probability Theory III
- Location:
- East Baltimore
- Term:
- 3rd term
- Department:
- Biostatistics
- Credits:
- 3 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- In-person
- Class Times:
-
- Tu Th, 3:30 - 4:20pm
- Auditors Allowed:
- Yes, with instructor consent
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Michael Rosenblum
- Resources:
- Prerequisite:
Calculus, real analysis; 140.721-2
- Description:
-
Presents the second part of the classical results of probability theory: central limit theorems, Poisson convergence, coupling, Stein-Chen method, densities, derivatives and conditional expectations.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Derive the probability distribution to which a sequence of distributions or a series converge
- Derive a bound on the distance between a random variable and a Poisson
- Define and derive conditional expectations
- Methods of Assessment:
This course is evaluated as follows:
- 50% Homework
- 50% Final-in-class exam
- 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 in-person section of a course that is also offered virtually/online. Students will need to commit to the modality for which they register.