140.646.01
Essentials of Probability and Statistical Inference I: Probability
- Location:
- East Baltimore
- Term:
- 1st term
- Department:
- Biostatistics
- Credits:
- 4 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- In-person
- Class Times:
-
- M W, 9:00 - 10:20am
- Auditors Allowed:
- Yes, with instructor consent
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Mei Cheng Wang
- Resources:
- Prerequisite:
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.
- Description:
-
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:
- Discuss the probabilistic foundation of modern statistics
- 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.