140.721.41
Probability Theory I
- Location:
- Internet
- Term:
- 1st 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
- Description:
-
Presents key concepts needed to understand measure-theoretic probability, including the following: set theory, limits of sequences, metric spaces, continuity of functions between metric spaces, convergence of sequences of functions, sigma algebras, probability measure. Emphasizes rigorous proof technique.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Write rigorous proofs.
- Rigorously define the probability measure corresponding to a given experiment
- Methods of Assessment:
This course is evaluated as follows:
- 100% Homework
- 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. Students who are able to be present in Baltimore for 1st term should register for this section. The course will include 30 minutes per week of lab (time TBA).