140.723.01
Probability Theory III
 Location:
 East Baltimore
 Term:
 3rd term
 Department:
 Biostatistics
 Credits:
 3 credits
 Academic Year:
 2022  2023
 Instruction Method:
 Inperson
 Class Times:

 Tu Th, 3:30  4:50pm
 Auditors Allowed:
 Yes, with instructor consent
 Undergrads Allowed:
 No
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructor:
 Contact:
 Abhirup Datta
 Resources:
 Prerequisite:
Calculus, real analysis; 140.7212
 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% Finalinclass 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 inperson section of a course that is also offered virtually/online. Students will need to commit to the modality for which they register.