140.723.41
Probability Theory III
- Location:
- Internet
- Term:
- 3rd term
- Department:
- Biostatistics
- Credits:
- 3 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Synchronous Online
- Class Times:
-
- Tu Th, 3:30 - 4:50pm
- Auditors Allowed:
- No
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Abhirup Datta
- Resources:
- Prerequisite:
Calculus, real analysis; 140.721-2
- Description:
-
Presents the second part of the classical results of probability theory: laws of large numbers, weak convergence, central limit theorems, conditional expectations and their properties.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Identify foundational concepts of probability theory
- Derive the limiting probability distribution of a sequence of distributions and its application to understanding large sample properties of statistical estimators
- Define and derive densities and their derivatives
- Identify conditional expectations, their properties and applications in regression method
- 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 virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.