140.734.01
Statistical Theory IV

Location
East Baltimore
Term
4th 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)
Michael Rosenblum
Contact Name
Michael Rosenblum
Frequency Schedule
Every Year
Prerequisite

Linear algebra; matrix algebra; real analysis; calculus; 140.731-33

Description
Focuses on the asymptotic behavior of estimators, tests, and confidence interval procedures. Specific topics include: M-estimators; consistency and asymptotic normality of estimators; influence functions; large-sample tests and confidence regions; nonparametric bootstrap
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Give conditions for consistency and asymptotic normality of M-estimators
  2. Determine the asymptotic distribution of M-estimators
  3. Construct tests and confidence regions for parameters of generalized linear models
  4. Determine when the nonparametric bootstrap is appropriate, and apply it in such cases
Instructor Consent
Consent required for some students
Consent Note
Consent required for any students who are not in the Biostatistics PhD program
Consent Contact
mrosenbl@jhsph.edu
Special Comments

One 1-hour lab per week