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Essentials of Probability and Statistical Inference II: Statistical Inference

East Baltimore
2nd term
4 credits
Academic Year:
2022 - 2023
Instruction Method:
Hybrid In-person and Synchronous Online
Class Times:
  • M W,  9:00 - 10:20am
Auditors Allowed:
Undergrads Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Charles Rohde

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 statistical inference. Includes the frequentist, Bayesian and likelihood approaches to statistical inference including estimation, testing hypotheses and interval estimation. 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. Describe the theoretical basis for the current methods used in statistical analysis
Methods of Assessment:

This course is evaluated as follows:

  • 50% 4-5 problem sets
  • 50% 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 virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.