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140.648.01 ESSENTIALS OF PROBABILITY AND STATISTICAL INFERENCE III: THEORY OF MODERN STATISTICAL METHODS

Department: Biostatistics
Term: 3rd term
Credits: 4 credits
Contact: Mei-Cheng Wang
Academic Year: 2014 - 2015
Course Instructor:
Description:

Builds on the concepts discussed in 140.646 and 140.647 to lay out the foundation for both classical and modern theory/methods for drawing statistical inference. Includes classical unbiased estimation, unbiased estimating equations, likelihood and conditional likelihood inference, linear models and generalized linear models, and other extended topics. De-emphasizes mathematical proofs and replaces them with extended discussion of interpretation of results and examples for illustration.

Learning Objective(s):
Upon successfully completing this course, students will be able to:
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
Location: East Baltimore
Class Times:
  • Tuesday 3:30 - 4:50
  • Thursday 3:30 - 4:50
Enrollment Minimum: 10
Instructor Consent: Consent required for all students

Consent required only for students who have not taken 140.646 and 140.647

For consent, contact: mcwang@jhsph.edu
Prerequisite:

Working knowledge of calculus

Auditors Allowed: Yes, with instructor consent
Grading Restriction: Letter Grade or Pass/Fail
Special Comments: One 1-hour lab per week (time TBA)