UNLV Department of Mathematical Sciences

STA 765: Statistical Decision Theory

Teaching & Class Materials

Welcome to the course homepage for STA761. If you are a student in this class you should check this site frequently for updated or new information.

graduate Program: (MS, PhD)

Related Course:  [STA715]   [STA761]

I. Outline of the Course

 

Instructor: Hokwon A. Cho, Ph.D., Associate Professor, Office: CDC 1008 (Building #10, Room 1008), Office phone: 895-0393 (Math. Sci. dept. office: 895-3567), E-mail: cho@unlv.nevada.edu.

Class Time and Location: Tu, Th 8:30 am - 9:45am, CBC C-TBA.

Office Hours: Tu & Th: 1:00 pm-3:00 pm or by appointment.

Textbook: Statistical Decision Theory and Bayesian Analysis, 2nd. Edition, by J. Berger, Springer-Verlag.

 

Scope of the Course: The course provides an overview of concepts and procedures on statistical decision-making under uncertainty. We examine its philosophy and develop the methods from the point of view of game theory, optimization and decision theory. The major topics will be covered are:

 

1.       Foundations of Statistical Decision Theory - Loss, Risk, Information, Decision rules/functions, Utility function, Completeness (Sufficiency), Invariance, Convexity, Admissibility, Minimax.

2.       Bayesian Methods - Elicitation of subjective probabilities, Priors and posteriors, Predictive distribution, Bayes rules/estimators, Bayesian testing, Empirical Bayes, Criticism.

3.       Sequential Analysis - Sampling strategies, Two-stage sampling, Sequential probability ratio test (SPRT), Bayesian sequential analysis.

4.       Multiple Decision Theory - Multiple Comparisons, Classification, Ranking and Selection.

5.       Recent Topics in Statistical Decision Theory - Statistical Learning and its Theory (- if time is permitted).

 

Homework: There will be roughly weekly assignments will be given in class (on a Tuesday) and expected to turn in on time. Some of them will be discussed in class.

 

Grading: The course grade is evaluated based upon the following components: Homework & assignments - 20%, Two tests (in class) - 25% each, Final Exam - 30%.

 

Exams: There will be two midterm exams most likely on 6th and 11th week. The final exam is scheduled according to the university calendars and schedules.

 

University Academic Policies on the Academic Misconduct, Copyright, Disability Resources Center (DRC), Tutoring, Writing Center, and Religious Holidays: click the next è University Academic Policies.

 

II. Textbook Information

 

Title:          Introduction to Statistical Decision Theory & Recent Development.

(Under Construction)

 

III. Bulletin Board

 

List of References and Further Readings for the course: click next è [List of Reference & Readings]

To see the lecture and homework schedule: click next  è [Lecture & HW schedule]

 

Announcements: 

1.       Welcome to STA 765.

 

IV. Handouts, Data Sets & Other Resources

 

Handouts & Statistical Tables:

§  Rain problems

 

Data Sets:

 

 

 

 

 

 

 

o    Statistical Software & Language:  | R | S-Plus | Minitab | SAS/JMP | SPSS | STATA | BMDP |

o    Search Journal Articles:           |JSTOR | MathSciNet | Ingenta | CIS  | Thomson | Wikipedia |

 

Ø  Journals:   | Statistics | Probability | Related Journals | Mathematics |

Ø  Societies:   | IMS | ASA | IMS BulletinSIAM | AMS | MAA |                    è More Link?

 

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Copyright © 2006-2018  Hokwon Cho. All Rights Reserved.