STAT 5380 -- Advanced Mathematical Statistics I -- Spring 2024


Basic Information

Course instructor: Dr. Alex Trindade, 233 Mathematics & Statistics Building.
E-mail: alex.trindade"at"ttu.edu; Phone: 834-6164.
Course Meets: TR 3:30 in Math 109.
Office Hours: TWR 1:00-2:00, or by appointment.

Text Books

Required (available as e-books through TTU library): Helpful:

Course Objectives, Syllabus, and Notes

STAT 5380 aims to provide a solid theoretical foundation for statistical inference (estimation and testing). It employs a probabilistic and measure theoretic approach to formulate and solve statistical inference problems. Material to be covered: sufficiency, decision theoretic statistical inference (minimax estimation, Bayes estimation, admissibility, shrinkage & bigdata, etc.), UMVUE, equivariance, information theoretic inference, large sample theory, asymptotic properties of maximum-likelihood methods, and optimal hypothesis tests (UMP, UMPU). This coverage corresponds to the following core topics: Prerequisites: STAT 5329 (Intermediate Mathematical Statistics II) and MATH 5382 (Advanced Probability I).

A detailed set of class notes covering the core is available here.

Expected Student Learning Outcomes

Students will learn the theory behind various statistical estimation and inference techniques, and will be capable of providing a solid theoretical justification and understanding for common statistical methods used in practice. Students can expect to spend several hours per week outside of instructional time on reading, homework, and exam preparation.

Methods of Assessing the Expected Learning Outcomes

The expected learning outcomes for the course will be assessed through: homework sets, semester tests, and a final exam. The course grade will be determined from homework problem sets (20%), two semester tests (25% each), and a comprehensive final exam (30%). The traditional grading scale will be used: The test schedule is as follows:

Homework Problem Sets

There will be weekly problem sets due on fridays, posted on Blackboard. You are expected to do all the assigned problems, but only a subset may actually be graded. Start each problem on a separate page. No late submissions will be accepted.

Note: problems with an asterisk (*) contain typographical errors, and you should refer to the above errata list for the correct versions.

Policies


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