140.734.01
Statistical Theory IV
Location
East Baltimore
Term
4th Term
Department
Biostatistics
Credit(s)
4
Academic Year
2024 - 2025
Instruction Method
In-person
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
Resources
Prerequisite
Linear algebra; matrix algebra; real analysis; calculus; 140.731-33
Focuses on the asymptotic behavior of estimators, tests, and confidence interval procedures. Includes specific topics: 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:
- Examine foundational concepts of statistical inference
- Give conditions for consistency and asymptotic normality of M-estimators
- Determine the asymptotic distribution of M-estimators
- Construct tests and confidence regions for parameters of generalized linear models
- Determine when the nonparametric bootstrap is appropriate, and apply it in such cases
Methods of Assessment
This course is evaluated as follows:
- 70% Homework
- 30% Take-home final exam
One 1-hour lab per week.