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Statistics 892
Applied Time Series Analysis
Spring 2007
Instructor
Name: Christopher R. Bilder, Ph.D.
Office: Hardin Hall 342D
Office hours: TR 10AM-10:45AM, W 1:30-2:30PM, and by appointment
Web portal: www.chrisbilder.com
E-mail: cbilder3@unl.edu
STAT 892 website:
statistics.unl.edu/faculty/bilder/ts or
www.chrisbilder.com/ts.
Textbook
Shumway, R. H. and Stoffer, D. S. (2006). Time Series Analysis and Its
Applications (2nd edition). Springer-Verlag: New York.
See the authors’ website at
http://www.stat.pitt.edu/stoffer/tsa2.
Supplementary:
Venables, W. N. and Ripley, B. D. (2002). Modern Applied Statistics with S
(4th edition). Springer-Verlag: New York. See Chapter 14.
Venables, W. N. and Smith, D. M. (2002). An Introduction to R. - PDF
version comes with R (Select HELP > MANUALS > AN INTRODUCTION TO R).
Prerequisite
STAT 870: Multiple Regression Analysis
STAT 882: Mathematical Statistics I – Distribution Theory, STAT 462:
Introduction to Mathematical Statistics I – Distribution Theory, or STAT 880:
Statistics and Applications
Grades
Grades will be based upon the following:
| |
Percent of grade |
| Test #1 |
25% |
| Test #2 |
25% |
| Final exam |
20% |
| Projects, Quizzes, etc... |
30% |
Grading
Scale:
| A |
³90%
and £100%
|
| B |
³80%
and <90%
|
| C |
³70%
and <80%
|
| D |
³60%
and <70% |
| F |
<60%
|
+ 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.
I recommend completing the projects in groups. If you do work in a group, all
group members are expected to participate equally and have a complete
understanding how to do all components of the projects. I reserve the right to
lower a student’s project grade if he/she does not abide by this group work
policy.
Students are required to turn in all projects electronically via the Blackboard
website for this course (use the digital drop box). Projects need to be
completed in Word documents and turned in BEFORE the time they are due. It is
your responsibility to make sure the project has been actually turned in.
Computer usage
The statistical computer 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.
All projects must be completed using R unless otherwise announced.
Final exam
The final exam is
scheduled for 10:00AM to 12:00PM on Thursday, May 3.
How to be successful in the course
To be successful in this
course, I strongly suggest that you should:
-
Take all exams
-
Complete all projects
-
Understand all the
material in the course lecture notes
-
Understand all R code and
calculations discussed during class
-
Complete all homework
-
Read the corresponding
sections of the textbook as we cover the course material
If you have problems with
completing any of the above, please ask questions in class or stop by during
my office hours.
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