Classroom and Computer Lab Section: Evans 344. Friday 9-11.
Course Outline:
An introduction to time series analysis in the time domain and
frequency domain. Topics will include: Stationarity,
autocorrelation functions, autoregressive moving average models,
partial autocorrelation functions, forecasting, seasonal ARIMA
models, power spectra, discrete Fourier transform, parametric
spectral estimation, nonparametric spectral estimation.
Text:
Time Series Analysis and its
Applications. With R Examples., by Robert H. Shumway
and David S. Stoffer. Springer. 2nd Edition. 2006. web site.
Prerequisites:
101, 134 or consent of instructor.
Assessment:
Lab/Homework Assignments
(25%): posted every one to two weeks, and due on Fridays at 9
(at the start of the section). The grade will be the average of
all homework grades except the worst.
Midterm Exams (30%):
scheduled for October 7 and November 9, at the usual lecture
time and place.
Midterm 1: pdf Solutions: pdf.
Midterm 2: pdf Solutions: pdf.
Project
(10%). Final Exam (35%):
scheduled for Friday 12/17/10.
Thursday, December 2: The final exam will be open book. There
will be five questions. You may answer all five if you wish. Your
grade will consist of the total from the best four questions.
Here are some review questions from Shumway and Stoffer for the material
since the second mid-term:
1.12, 1.13, 4.16, 4.18a, 4.32, 4.33.
Partial solutions (to 1.12-4.18a): pdf
Tuesday, November 16: Homework 5's due date has been extended to
11am on Tuesday, November 23, 2010, in 399 Evans.
Wednesday, November 3: Homework 5 has been posted.
It is due at 9am on Friday, November 19, 2010, in 344 Evans.
The second mid-term exam will cover all
material up to and including the lecture on Tuesday, November 2.
There will be 3 questions. You should answer all questions. Each
part of each question will have a percentage written next to it -
the percentage of the grade that it constitutes.
Here are some review questions from Shumway and Stoffer for the
material since the first mid-term:
4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.21, 4.23, 4.24.
Thursday, October 28: Remember that the second mid-term
exam will be in class (12:30-2:00) on Tuesday, November 9.
Like the first mid-term, it will be an open-book exam:
you can bring any material you like.
Exam papers will be handed out at 12:40, the exam will go from
12:45 to 1:55.
Thursday, October 21:
If you are looking for ideas for the project, there is a large
collection of time series
here.
Tuesday, October 19:
Information about the project has been posted
here. A one-paragraph proposal is due on
Wednesday, November 3. Please email it to bartlett at stat.
Thursday, September 30: The first mid-term exam will cover all
material up to and including today's lecture. Here are some review
questions from Shumway and Stoffer:
1.4, 1.5, 1.6, 1.9, 1.15, 1.16a, 2.6,
3.1, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.10, 3.11, 3.23a.
Monday, September 27: Remember that the first mid-term
exam will be in class (12:30-2:00) on Thursday, October 7.
It will be an open-book exam: you can bring any material you like.
Exam papers will be handed out at 12:40, the exam will go from
12:45 to 1:55. There will be 6 questions. You may answer all
six if you wish; your grade will consist of the total from the
best five questions. Each part will have a percentage written
next to it - the percentage of the grade that it constitutes.
Please take notice of this. The percentages reflect the
relative significance of the relevant material, not how much
time it will take to answer the question.
Monday, August 30: Some R resources referred to in the first computer
lab:
Tuesday, August 24: To sign up for computer accounts, you will
need to obtain a form from Joe. At the first lab section, on this
Friday, August 27, Joe will have these forms available, and will
also present an introduction to R.
Collaboration:
You are encouraged to work in small groups on homework problems; it's
an excellent way to learn. However, you must write up the solutions on
your own, and you must never read or copy the solutions of other
students. Similarly, you may use books or online resources to help
solve homework problems, but you must credit all such sources in your
writeup and you must never copy material verbatim.
Academic Dishonesty:
Any student found to be cheating risks automatically failing the class
and being referred to the Office of Student Conduct. In particular,
copying solutions, in whole or in part, from other students in the class or
any other source without acknowledgment constitutes cheating.