140.722.01
Probability Theory II
Location
East Baltimore
Term
2nd Term
Department
Biostatistics
Credit(s)
3
Academic Year
2024 - 2025
Instruction Method
In-person
M, W, 1:30 - 2:50pm
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
Calculus, real analysis, 140.721
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:
- Examine and apply foundational concepts of probability theory
- 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)