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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
Academic Year:
2014 - 2015
Location:
East Baltimore
Class Times:
  • Tu Th,  3:30 - 4:50pm
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Mei-Cheng Wang
Course Instructor:

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Prerequisite:

Working knowledge of calculus

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 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 all students

Consent Note:

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

For consent, contact:

mcwang@jhsph.edu

Special Comments:

One 1-hour lab per week (time TBA)