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Essentials of Probability and Statistical Inference I: Probability

Course Status

1st Term
Academic Year
2023 - 2024
Instruction Method
Synchronous Online
Class Time(s)
M, W, 9:00 - 10:20am
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year

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
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.