140.721.01
Probability Theory I
Location
East Baltimore
Term
1st Term
Department
Biostatistics
Credit(s)
3
Academic Year
2019 - 2020
Instruction Method
TBD
Tu, Th, 3:30 - 4:50pm
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
Presents the first part of the classical results of probability theory: measure spaces, LP spaces, probability measures, distributions, random variables, integration, and convergence theorems.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Rigorously define the probability measure corresponding to a given experiment
- 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
The course will include 30 minutes per week of lab (time TBA)