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Essentials of Probability and Statistical Inference I: Probability

East Baltimore
1st term
4 credits
Academic Year:
2022 - 2023
Instruction Method:
Class Times:
  • M W,  9:00 - 10:20am
Auditors Allowed:
Yes, with instructor consent
Undergrads Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Mei Cheng Wang

Working knowledge of linear algebra, including the ability to invert a matrix; full year college level calculus, plus current working knowledge of it, meaning you can quickly do integration and differentiation of standard functions, which are needed for homework and exam questions.


Introduces students to the theory of probability and the formal language of uncertainty. Includes the basic concepts of probability; random variables and their distributions; joint, marginal and conditional distributions; independence; distributions of functions of random variables; expectations; moment generating functions; probability and expectation inequalities; convergence concepts and limit theorems; order statistics. Emphasizes rigorous analysis (including proofs), as well as interpretation of results and simulation for illustration.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Discuss the probabilistic foundation of modern statistics
  2. Solve basic probability problems
Methods of Assessment:

This course is evaluated as follows:

  • 60% 6 problem sets
  • 40% Final Exam

Instructor Consent:

Consent required for some students

Consent Note:

Course intended for Biostatistics ScM and MHS candidates only; consent needed for anyone who is not a Biostatistics PhD, ScM, or MHS student.

For consent, contact:

Special Comments:

Please note: This is the onsite section of a course that is also offered virtually. Students will need to commit to the modality for which they register.