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Essentials of Probability and Statistical Inference IV

East Baltimore
4th term
4 credits
Academic Year:
2019 - 2020
Class Times:
  • M W,  10:30 - 11:50am
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor :
Daniel Scharfstein

140.646-648 or 140.611-12 or 140.621-24 or 140.651-54 or 140.671-74; working knowledge of calculus


Builds on the concepts discussed in 140.646 and 140.647 to lay out foundation for both classical and modern theory/methods for drawing statistical inference. Includes classical unbiased estimation, unbiased estimating equations, likelihood and conditional likelihood inference, information theory and other extended topics. Includes mathematical proofs but will not emphasize highly technical details. Extended discussion, interpretation of results, and examples for illustration will be provided.

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:

Method of student evaluation based on 4-5 problem sets and a final exam

Instructor Consent:

Consent required for some students

Consent Note:

Consent required only for students who

have not taken 140.646, 140.647, and 140.648

For consent, contact:

Special Comments:

One 1-hour lab per week (time TBA)