STAT 5380 -- Advanced Mathematical Statistics I -- Spring 2018

Basic Information

Course instructor: Dr. Alex Trindade, 228 Mathematics & Statistics Building.
E-mail: alex.trindade"at"; Phone: 834-6164.
Course Meets: MWF 1:00-1:50 in MATH 010.
Office Hours: MWF 9-12 in 201F, or by appointment.

Text Book

Required (available as e-book 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. 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 thursdays. You are expected to do all the assigned problems, but only a subset may actually be graded. Start each problem on a separate page. All work handed in must be stapled together. 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.


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