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140.648.01
Essentials of Probability and Statistical Inference III: Theory of Modern Statistical Methods

Location
East Baltimore
Term
3rd Term
Department
Biostatistics
Credit(s)
4
Academic Year
2018 - 2019
Instruction Method
TBD
Class Time(s)
M, W, 10:30 - 11:50am
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
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.
Special Comments

One 1-hour lab per week (time TBA)