140.721.01
Probability Theory I
- Location:
- East Baltimore
- Term:
- 1st term
- Department:
- Biostatistics
- Credits:
- 3 credits
- Academic Year:
- 2019 - 2020
- Class Times:
-
- Tu Th, 3:30 - 4:50pm
- Auditors Allowed:
- Yes, with instructor consent
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor :
- Contact:
- Michael Rosenblum
- Resources:
- Prerequisite:
Calculus, real analysis
- Description:
-
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
- Methods of Assessment:
Homework (50%), Midterm exam (20%), final exam (30%)
- 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:
The course will include 30 minutes per week of lab (time TBA)