Cleveland State University
Mathematics Department
MTH 421 (3 credit) / MTH 521 (4 credit)
Time Series Analysis
Syllabus - Spring 2015
How can you contact me?
------------------------------------------------------------------------Sandra Hurtado Rúa. Ph.D.
Office:
Rhodes Tower 1515
Office Phone: 216 523 7324
Office Hours: Mondays
3 -3:50 PM
Wednesdays 3 -3:50 PM
And by appointment.
website:
http://facultyprofile.csuohio.edu/csufacultyprofile/detail.cfm?FacultyID=s_hurtadorua
E-mail:
S.HURTADORUA@csuohio.edu
If you email me, please write on your subject line MTH421/521. This will help me
prioritize emails from the class and reply to you quickly.
Basic Course Information:
------------------------------------------------------------------------Section:
MTH 421/521
Class Meetings:
Mondays and Wednesdays 4:00 -5:50 PM
Classroom:
RT 1501
Class website:
Blackboard
Textbook:
Forecasting, Time Series, and Regression, 4th edition by Bowerman,
O’Connell, and Koehler
Software
SAS and R
Final Exam:
For MTH 421: Mon, April 13
For MTH 521: Mon, May 4
Prerequisite:
For MTH 421: MTH 347 with a grade of "C" or better or permission of
instructor. For MTH 521: MTH 567 or permission of instructor.
Drop Dates:
January 23 (drop) and March 27 (withdrawal with a “W”)
What is this course about?
------------------------------------------------------------------------The course will cover techniques of modeling data that are collected sequentially. Topics to be
covered include a review of basic ideas of modeling a continuous variable, time series regression,
autocorrelation, decomposition methods, exponential smoothing, nonseasonal and seasonal BoxJenkins models. The course will use a statistical programming language. Data from a variety of
fields will be studied
What will you be able to do at the end of the semester?
------------------------------------------------------------------------Statistics are used in almost any field, and the ideas presented in this class will help you interpret
and critique arguments using statistics. In particular, upon completion of this course, you will
become proficient in:
• Time series models and their implications.
• Sequential data summaries and plots.
• Time series models using regression, decomposition methods, exponential smoothing,
nonseasonal and seasonal Box-Jenkins methods, and advanced Box-Jenkins methods.
• Estimation and forecast of time series models.
• Diagnostic checking of time series models.
• Time series analysis using R, SAS or Minitab.
Classroom Etiquette:
------------------------------------------------------------------------My goal is to have a classroom atmosphere that allows the class to learn the material without
distractions. The following behaviors will help achieve this:
• Students are strongly encouraged to attend all class meetings. Students tend to do well in
the tests if they do not miss many classes.
• Attendance sheets will be passed around most class days.
• Please arrive to class on time.
• Please use respectful language.
• Please turn off your cell phones before coming to class.
• Students are also expected to be aware of any changes in the dates of assignments/tests.
• If you are late to class or leave early, please do with minimal disruption to the classroom
environment.
• Students are expected to be aware of any changes in the dates of assignments or tests.
• Printed handouts will only be available the day they are handed out.
• Disruptive behavior will not be tolerated. Disruptive behavior is behavior that interferes
with the classroom and the ability of others to get their work done.
• All cell phones should be turned-off or placed on vibrate during class. Text messaging
during class is not appropriate.
• During computer lab sessions, checking email and surfing the web is inappropriate when
the instructor is talking.
Graduate (MTH521) vs. Undergraduate (MTH421)
------------------------------------------------------------------------Graduate students are expected to complete all the assignments that are made to the
undergraduates and engage in reporting at a more advanced level. They will also complete
additional statistics topics, will use additional software packages, and may have challenge
problems on the assessments. Graduate students and undergraduate students will have a
different schedule.
Assignments, Test and Grading Scheme: -----------------------------------------------------------------------The grading will be as follows:
MATH 421
MATH 521
Homework assignments
50%
30%
Midterm exam 1
20%
20%
Midterm exam 2
N/A
20%
30%
30%
Final Exam
Final grades cutoffs for MATH 421: (92% A, 90% A-, 88% B+, 82% B, 80% B-, 78% C+,
70% C, 60% D, and < 60% F). Grades will be available on Blackboard.
Final grades cutoffs for MATH 521: (90% A, 80% B, 75% B-, 70% B, and < 70% C).
Grades will be available on Blackboard.
Homework assignments:
Homework will consist of practice problems and homework assignments. Practice Problems may
be assigned, but these will not be graded and will not be required to be handed in. You are
strongly recommended to complete these problems. Homework Assignments will be assigned
in advance, collected and graded. You should expect about 5 assignments. Some problems will
require computer analysis/software manipulation. All work and output must be shown to receive
credit. Homework assignments need to be turned in on paper - electronic copies will not be
accepted. The homework deadline will be strictly adhered to. A deduction of 10% per day
(weekends count as one day) will result assignments turned in after 4pm of the due date.
Graduate students should expect extra problems or additional difficulty on some of their
assignments.
Midterm Exam(s):
Undergraduate students (MTH 421) will have only one midterm exam while graduate students
(MTH 521) will have two midterm exams. They may consist of an in-class and a take-home part.
Students who know they will miss the exam are required to let the instructor know prior to the
scheduled exam time. Make-up exams are not guaranteed. If you forget your text or calculator,
you cannot expect the instructor to provide resources. The in-class exam is open book and open
notes - however, you should prepare as if that is not the case. Graduate students should expect
additional questions on each exam.
Final Exam:
The final exam will consist of an in-class and a take-home part and it will be comprehensive. The
exam will cover material discussed in class that may not be covered in the text. In addition, some
techniques or procedures may be taught in class differently than what appears in the text. You are
responsible for all material covered in class. Make-up exam will not be given. Cell phone
calculators are not permitted for use on exams. All in class examinations are open book.
Attendance:
Attendance will be taken daily. Attendance can impact your grade: If you have less than four
session absences (excused or unexcused), you can drop your lowest homework score.
Tips for Success: DO NOT WAIT TO GET HELP!
------------------------------------------------------------------------• Come to class. This point cannot be overemphasized. When you attend class, you are
being exposed to the material at a steady rate, you can take notes, gain a feel for what is
being emphasized, get tips for tests, etc.
• Read the book. Make sure to understand the concepts involved. By reading the book
you will gain another perspective than the one I present in the lecture.
• Ask questions. Ask questions during class if there is something you do not understand. If
you have a question, there is a good chance that other students are wondering about the
same thing.
• Come see me. Make an appointment to get help. Come prepared with questions and with
work so that I can see how far you are able to get with the problems.
• Work with each other. Working on homework together is an effective way to work
through difficult sticking points. You are strongly encouraged to form study groups during
the first few weeks of the course. You must each write up and hand in your own work
though.
• Mathematical Assistance Center. If you need (free) mathematical tutoring, contact the
Mathematics Assistance Center at Main Classroom Building 230 (
http://www.csuohio.edu/sciences/dept/mathematics/learning_center.html )
Academic Integrity:
------------------------------------------------------------------------Acts of academic dishonesty (cheating, plagiarism-includes not citing sources, submission of work
for more than one class, fabrication, fraud, etc.) are expressly forbidden. Infringements will be
dealt with according to CSU policy. If cheating occurs, the student will receive a grade of 0 for
that component of the course. Information regarding the official CSU policy regarding cheating
and plagiarism can be found in the CSU Code of Student Conduct at
www.csuohio.edu/studentlife/StudentCodeOfConduct.pdf
Students with disabilities:
------------------------------------------------------------------------Students with documented disabilities are entitled to reasonable accommodations if needed. If
you believe you need accommodations, please see the Office of Disability Services at 216-6872015 in MC 147 (www.csuohio.edu/offices/disability).
Technology and supplies:
------------------------------------------------------------------------Blackboard: Classroom resources will be posted here.
Statistical Packages: Many of the assignments and exams will require the use of computer
software. I will provide some software code. Learning how to use the software is a part of the
course. We will be using Minitab 17, R and the SAS software system. You will need access to
software outside of class. Minitab 17 will be available on Blackboard (as a zipped file)- installation
instructions will be provided. Information about R and SAS will be provided in separate handouts.
Class Supplies: Please bring your textbook to each class. I recommend to have a USB drive to
store your class work. Additional handouts may be supplied in class; you are responsible for
receiving and keeping these materials.
Disclaimer: The instructor reserves the right to make any changes she considers
academically advisable. It is the student responsibility to attend classes and keep track of
the proceedings.
Tentative Schedule:
------------------------------------------------------------------------A tentative schedule is posted and updated using Blackboard. Changes to this schedule will be
announced in class. It is the student’s responsibility to attend class and be aware of any changes
to the schedule.
Week
Date
Chapter / Activities
1
Jan 12 -14
Chapter 1. Introduction
2
Jan 21
Chapters 2-5. Review of regression analysis.
3
Jan 26 -28
Section 6.1. Modeling trend by using Polynomial functions.
4
Feb 2 -4
Section 6.2. Detecting Autocorrelation.
Section 6.3. Types of Seasonal Variation
Homework assignment # 1 is due on Monday, Feb. 2 and will be
posted on Tuesday, Jan. 27
5
Feb 9 -11
Section 6.4. Modeling Seasonal variation with dummy variables.
Section 6.5. Growth Curve Models.
6
Feb 18
Section 6.6 Handling first Order Autocorrelation
Homework assignment # 2 is due on Wednesday, Feb. 18 and
will be posted on Tuesday, Feb. 10
7
Feb 23-25
Section 7.1 Multiplicative Decomposition
Review
8
Mar. 2
MTH 421 and MTH 521 Midterm #1 (1 hour)
Section 7.2 Additive Decomposition
Mar 4
9
10
Section 7.3 The X-12 ARIMA Seasonal Adjustment Method
Spring break (03/08/15 - 03/15/15)
Mar 16 -18
Section 8.1 Simple Exponential Smoothing
Section 8.2 Tracking Signals
Homework assignment # 3 is due on Monday, Mar. 16 and will be
posted on Tuesday, Mar. 3.
11
Mar 23 -25
Section 8.3 Holt’s Trend Corrected Exponential Smoothing
Section 8.4 Holt-Winters Methods
Homework assignment # 4 is due on Monday, Mar. 23 and will be
posted on Tuesday, Mar. 17
12
Mar 30 -Apr 1
Section 8.5 Damped Trend and Other Exponential Methods
Section 9.1 Stationary and Nonstationary Time Series
13
Apr 6 -8
Section 9.2 The SAC and SPAC
Review
Homework assignment # 5 is due on Monday, Apr. 6 and will be
posted on Tuesday, Mar. 31
14
15
Apr 13
MTH 421 Final Exam
4:00 – 5:50 pm
MTH 521 Midterm #2
4:00 – 5:10 pm
Apr 15
Section 11.1 Transforming a seasonal time series into stationary series.
Apr 20 -22
Section 12.1 General seasonal model
Section 12.2 Intervention models
16
Apr 27 -29
Section 12.3 Building a transfer function model
Review
May 4
MTH 521 Final – 3:45 - 5:45pm