Advanced Statistical Inference - II
Spring Session, 2009
(a pdf version of syllabus)


ST794: Advanced Statistical Inference - II


TH from 10:15 to 11:30 a.m.


232 Daneils Hall

. .


Sujit Ghosh





220C Patterson Hall

Office hours:

Tue/Thu 3:00 - 4:00 p.m. or by appointment

. .


Jiangtao Duan





Statistics Tutorial Center, Bureau of Mines 110

Office hours:

Wednesday 1:00 - 3:00 p.m. or by appointment

Class links: Lectures & Assignments| Ask a question (use Message board)

Course prerequisite: ST793 and corequisite: ST778

Text: Jun Shao (2003). Mathematical Statistics, 2nd Edition. Springer Verlag. (ISBN:0387953825)

Homework: Homework will normally be assigned (as indicated on the homework page) at the end of class on Thursdays. Unexcused late homework will not be accepted. The final homework average will be computed after dropping the two lowest grades.

Examinations: Examinations will be closed book and closed notes. However students will be permitted to bring one 8.5 by 11 inch sheet of notes to the midterm exam and two to the final exam. The final exam will be cumulative, but weighted toward the materials covered after the midterm.

Exam schedule:
Midterm exam
Tuesday, Mar 10
10:15-11:30 a.m.
Syllabus: Sections 2.1-2.3, 3.1, 3.2, 4.1, 4.3
Final exam
Tuesday, May 5
8:00-11:00 a.m.
Syllabus: All of above + Sections 5.1 and additional notes

Asking questions: If you have questions about lectures, homework assignments, exams, procedures or any other aspect of the course please log onto, and click on "Message Board". Then click on "Post New Topic", enter your question in the Message box, and click on "Submit Message". You will receive a response from me or another student. Everyone in the class will be able see your question and the response.

Anonymous mail: If you wish to send me an anonymous suggestion or reminder, send email to The system will remove mail headers, but you must remember to remove your signature and other identifying information.

Grading System: Final grade will be based on:

Final Semester Score = (2xHW + CP + 8xME + 9xFE)/20

where HW is the homework average (out of 100) after dropping the two lowest scores, CP is based on class participation and ME and FE are the scores (out of 100) on the midterm and the final exams, respectively. Grades will be assigned on the +/- scale.

Auditing: Auditors are expected to attend class regularly and submit homework on the same schedule as the other students. The final grade for auditors (AU or NR) will be based on their final homework average after dropping the two lowest scores. An average homework score of 75 or better is required for an AU.

Policy on Academic Integrity: The University policy on academic integrity is spelled out in Code of Student Conduct. For a more though elaboration see the NCSU Office of Student Conduct website. For this course group work on homework is encouraged. However copying someone else's work and calling them your own is plagiarism, so the work you turn in should be your own.

Students with Disabilities: Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, students must register with Disability Services for Students (DSS), 1900 Student Health Center, CB# 7509, 515-7653.

Reference material (Have requested these be on reserve at DH Hill Library):

Bickel, P. J. and Doksum, K. A. (2001). Mathematical Statistics vol. I, 2nd Edition. Prentice Hall

Gyorfi, L., Kohler, M., Krzyzak, A., Walk, H. (2002). A Distribution-Free Theory of Nonparametric Regression Springer Verlag

Lehmann, E. L. (1997). Testing Statistical Hypotheses, 2nd Edition. Springer Verlag

Lehmann, E. L. and Casella, G. (2001). Theory of Point Estimation, 2nd Edition. Springer Verlag

Course objectives:

This course is the second semester of a two-course sequence, ST793-4, covering a medley of advanced statistical inferencial methods. The objective of this course, ST794, is to develop an advanced-level understanding and working knowledge of statistical inference.
The course provides an introduction to the rudiments of statistical inference for population parameters based on a general decision theoretic framework covering estimation and test of hypothesis. Some nonparametric methods will also be introduced. Concepts, methods and theory are emphasized, rather than applications. Successful completion of this course will provide you with a foundation for understanding probability-based statistical inference material presented in other courses.

Students taking the course will have completed both ST793, and ST778.

Syllabus: In ST794 we shall complete the following concepts.
  • Statistical Models: Parametric, Nonparameteric, Semiparamtric, Identifiability, Exponential family, Location-scale family and Mixture distributions
  • Principles of Mathematical Statistics: Sufficiency, Completeness, Ancillarity, Invariance and Unbiasedness
  • Statistical Decision Theory: Loss functions, Risk functions, Admissibility, Minimaxity, Bayes rules
  • Information Criteria: AIC, TIC and BIC
  • Non-parametric Methods: Empirical distribution, Empricical likelihood, Density estimation, Nonparametric regression

Last updated on: Jan 08, 2009