STATISTICS 689 Introduction to Applied Bayesian Methods Fall ...

STATISTICS 689
Introduction to Applied Bayesian Methods
Fall Semester, 2012
Instructor
Office
Jeff Hart
459E Blocker Building
Phone 979-845-1467
Email
Office hours
Course website
Prerequisites
Text
hart@stat.tamu.edu
10:30-11:30 MW, 9:00-10:00 F, or by appointment
We will use the DOSTAT course management system. I have
sent you information on how to register for DOSTAT.
STAT 604 – Statistical Computation
STAT 608 – Regression
STAT 630 – Overview of Mathematical Statistics
Peter D. Hoff, A First Course in Bayesian Statistical Methods
Course Description
This course is concerned with Bayesian statistics, which is a particular approach to statistical
inference that differs philosophically and operationally from the classic frequentist approach. After
defining Bayesian inference, its advantages will be discussed, and its application illustrated using
some classical models, including binomial, Poisson and normal data, the multivariate normal model
and linear regression. Hierarchical models are also defined and discussed. Bayesian inference is
based on a so-called posterior distribution, which can only be computed exactly in relatively simple
cases. Therefore, a modern method of approximating posteriors, known as Markov Chain Monte
Marlo, is treated.
Course Objectives
The objective of this applied master’s level course is to introduce students to the Bayesian paradigm
for data analysis. Students learn how uncertainty regarding parameters can be explicitly described
as a posterior distribution that blends information from a sampling model and a prior distribution.
Students are exposed to foundational principles, but the course emphasizes modeling and
computations under the Bayesian paradigm.
Course Outline
The course will follow the textbook fairly closely, covering Chapters 1-11.

Homework
About ten homework assignments will be made over the course of the semester. Distance students
will submit their homework via WebAssign. Local students may either submit their homework in
class or email it to me. I may not grade every homework problem, but feel free to discuss any of the
problems with me. You may consult with other students about the homework, but always write
up solutions by yourself. You should never just copy from another person or any other source.
Exams
You will have two midterm exams, which are tentatively scheduled for Wednesday, October
3 and Wednesday, November 14. Local students will take the exams during the usual class
time, and distance students will take the exams via the proctoring system used by all of the
department’s distance courses. Effective Fall 2012, all students in Section 700 who are not
receiving their complete degree in an online program (both STAT and non-STAT)
must take the exam at the same date and time as the on campus students. Students
must verify through an email to Penny Jackson that they are receiving their complete
degree in an online program in order to take the exam outside the scheduled oncampus
exam time. Please note the exam dates and times provided and make any
special arrangements if necessary.
Project
Each student will choose a data set, which could come from his/her own research, or the internet.
The student will develop a Bayesian model for the data, and carry out an analysis of it. Good
projects will require significant effort throughout the semester and will result in a substantial
written report. More details will be given subsequently.
Grading Policy
The weights given to the four parts of the course are as follows:
25% – Homework
25% – Midterm 1
25% – Midterm 2
25% – Project
Grades will be assigned using the traditional scale:
A – 90 ≤ average ≤ 100
B – 80 ≤ average < 90
C – 70 ≤ average < 80
D – 60 ≤ average < 70
F – 0 ≤ average < 60
Please note, however, that I might lower the cutoffs. This would be done to make the discrepancy
between, for example, an A and a B as large as possible.

University Excused Absences
Definition: Details of what constitutes a University Excused Absence are available in the
Student Rules (http://student-rules.tamu.edu/).
Homework: Late homework is only accepted in the case of a University Excused Absence.
Exams: Quoting from the University Excused Absence (http://student-rules.tamu.edu/
rule07) section of the Student Rules, “To be excused the student must notify his or her
instructor in writing (acknowledged e-mail message is acceptable) prior to the date of absence
if such notification is feasible. In cases where advance notification is not feasible (e.g. accident,
or emergency) the student must provide notification by the end of the second working day
after the absence. This notification should include an explanation of why notice could not
be sent prior to the class. If needed, the student must provide additional documentation
substantiating the reason for the absence, that is satisfactory to the instructor, within one
week of the last date of the absence.” In short, if you are unable to take an exam at the
scheduled time you must notify me (Dr. Hart) as soon as possible. Missed exams will be given
zero points except for a University Excused Absence. In the latter case, I will administer a
makeup exam.
Incomplete Grade: An incomplete grade will be given only if a student, due to a University
Excused Absence, is missing one component of the course grade.
STATEMENT ON DISABILITIES
The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides
comprehensive civil rights protection for persons with disabilities. Among other things, this legislation
requires that all students with disabilities be guaranteed a learning environment that provides
for reasonable accommodation for their disabilities. If you believe you have a disability requiring
an accommodation, please contact the Office of Disabilities Services in Room B118, Cain Hall.
The phone number is 845-1637.
STATEMENT ON PLAGIARISM
The handouts used in this course are copyrighted. By ”handouts,” I mean all materials generated
for this class, which include but are not limited to syllabi, quizzes, exams, lab problems, in-class
materials, review sheets, and additional problem sets. Because these materials are copyrighted,
you do not have the right to copy the handouts, unless I expressly grant permission. As commonly
defined, plagiarism consists of passing off as one’s own ideas, words, writing, etc., which belong
to another. In accordance with this definition, you are committing plagiarism if you copy the
work of another person and turn it in as your own, even if you should have the permission of that
person. Plagiarism is one of the worst academic sins, for the plagiarist destroys the trust among
colleagues without which research cannot be safely communicated. If you have any questions
regarding plagiarism, please consult the latest issue of the Texas A&M University Student Rules,
under the section ”Scholastic Dishonesty.”
ACADEMIC INTEGRITY STATEMENT
“An Aggie does not lie, cheat, or steal or tolerate those who do.”
Information about the Honor Council Rules and Procedures can be obtained at the web site:
www.tamu.edu/aggiehonor. If an instructor encounters a student cheating or not abiding by
university rules then it is mandatory that the instructor report the student to the Aggie Honor
System Office: complete information at http://www.tamu.edu/aggiehonor.