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140.771.01
Advanced Statistical Theory I

Course Status
Discontinued

Location
East Baltimore
Term
1st Term
Department
Biostatistics
Credit(s)
4
Academic Year
2022 - 2023
Instruction Method
In-person
Class Time(s)
Tu, Th, 1:30 - 2:50pm
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 Other Year
Prerequisite

Real Analysis, Measure-Theoretic Probability, Introduction to Statistical Theory I-II

Description
Focuses on drawing large sample inferences about "parameters" in statistical models. Develops asymptotic theory for maximum likelihood estimation, M-estimation, and generalized method of moment (GMM) estimation. Discusses formal techniques for constructing estimators in semi-parametric models. Pays particular attention to models for longitudinal and survival data. Special topics presented by guest lecturers. Involves rigorous mathematical arguments so that familiarity with concepts in advanced calculus, real analysis, and measure theory will be required.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Understand large sample theory underlying commonly used statistical procedures such as maximum likelihood, M-estimation, and GMM-estimation.
  2. Understand the foundations of semi-parametric inference.
  3. Understand the foundations of the counting process approach to survival analysis.
Multiterm
Final grade applies to all terms