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KSU STAT 904: Resampling Methods
UNL STAT 950: Bootstrap Methods and their Application
Spring 2008
Instructor
Name: Christopher R. Bilder, Ph.D.
Office: UNL Hardin Hall 342D on east campus
Office hours: M 9-10AM and WF 1:45PM-2:45PM in my office and at breeze.unl.edu/boot, by
appointment
Website: www.chrisbilder.com
E-mail:
Phone: see printed syllabus
Course website: statistics.unl.edu/faculty/bilder/boot or
www.chrisbilder.com/boot
Textbooks
Davison, A. C. and Hinkley, D. V. (1997). Bootstrap Methods and their
Application. New York: Cambridge University Press.
Supplementary:
Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap.
Chapman & Hall: New York.
Venables, W. N. and Ripley, B. D. (2002). Modern Applied Statistics with S
(4th edition). Springer-Verlag: New York.
Venables, W. N. and Smith, D. M. (2007). An Introduction to R. - PDF version
comes with R (Select HELP > MANUALS > AN INTRODUCTION TO R).
There are many other books on the bootstrap! I recommend investigating others
as needed. Other books include Hall’s (1992, 1997) The Bootstrap and Edgeworth
Expansion which is more theory based than our book and Lunneborg’s (2000)
Data
Analysis by Resampling: Concepts and Applications which is a lower level book
than Davison and Hinkley.
Prerequisites
KSU: STAT 771 and STAT 860
UNL: STAT 883, STAT 870 or 970, prior experience with R software
Grades
Grades will be based upon the following:
| |
Percent of grade |
| 1 Final exam |
20% |
| 1 Mid-term |
20% |
| Participation |
5% |
| Presentation |
15% |
| Projects, Quizzes, etc... |
40% |
Grading Scale:
| A |
³90%
and £100%
|
| B |
³80%
and <90%
|
| C |
³70%
and <80%
|
| D |
³60%
and <70% |
| F |
<60%
|
For UNL students:
+ and – letter grades are 2.5%
from the above cut off points. For example, A- is 90-92.5% and B+
is 87.5-90%.
A project completed in an unreadable or unprofessional manner will be
returned to the student. The project may be redone and turned in again; however,
points will be deducted from the grade. No late projects, quizzes, etc. will be
accepted.
You are required to turn in all projects electronically. E-mail projects to me
in Word documents BEFORE the time the project is due. I will e-mail you an
acknowledgement if it has been received. If you do not receive an e-mail
acknowledgement from me, it is your responsibility to determine what happened to
the project.
Computer Usage
The statistical software package, R, will be used extensively
to do calculations in this class.
R is available for free from
www.r-project.org. The specific
link to download the Windows version is
cran.r-project.org/bin/windows/base
and to obtain various add-on packages is
cran.r-project.org/src/contrib/PACKAGES.html.
This software is based on the syntax used in the
award winning S language
and is very similar to the
S-Plus
statistical software package. The bootstrap functions described in Chapter
11 of the book are available in R’s boot package.
All projects must be completed using R unless otherwise announced.
Final Exam
Due to the different finals week dates for KSU and UNL, the final exam will
be Tuesday, May 6 during our normal class time.
Expectations of Students
Students are expected to read the corresponding sections of the textbook.
This can be a difficult book, and it may take more than one read through to
understand the topics discussed. Outlining the textbook is one way to help with
your reading. Also, students are responsible for all material in the lecture
notes unless otherwise stated during class. I recommend re-running all of my R
programs one line at a time to make sure you understand its content. The
bootstrap would not be very useful without a computer so there will be emphasis
in the class on computer work.
Word version of the
syllabus
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