MATH 372 — Mathematical Modeling I
Fall 2007
TIME and LOCATION:
Mon Wed Fri
12:00--12:50,
NRE 2 020
INSTRUCTOR:
Dr. Petro Babak
OFFICE:
CAB551,
EMAIL:
petro@math.ualberta.ca
Please include "MATH 372" in the subject line of any email you send to me.
OFFICE HOURS:
10:30-11:30 Wednesday or by appointment
COURSE WEB PAGE:
http://www.ualberta.ca/~petro/MATH372.html
Phone: (780) 492-3912
COURSE DESCRIPTION:
This is a project-oriented course offering the opportunity to discover how a variety of real-world problems
can be described and analyzed with the aid of simple mathematical models and computer simulations. This
includes the following:
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ability to translate real-world problems into mathematical equations (the model);
ability to solve the model (in conjunction with appropriate computational methods);
ability to interpret the mathematical solution in terms of the real-world application;
ability to assess the strengths and weaknesses of the model and the information obtained from it.
The following main categories of models will be covered:
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optimization models (topics include one-variable optimization, constrained and unconstrained multivariable optimization, sensitivity analysis, linear programming, symbolic computation);
dynamical models (topics include discrete and continuous models, steady states, stability analysis,
phase plane analysis, periodic behaviour, numerical simulation);
probabilistic models (topics include discrete and continuous distributions, Markov chains and
Markov processes, linear regression, Monte Carlo simulation).
TEXT BOOK: None required. Topics will be drawn from several different books.
GROUP PROJECTS:
 Each student will participate in teams and work on two extended modeling projects.
 I provide suggestions for projects, but teams may develop their own project (these must be approved
by me).
 Each team will hand in a report on their project. Only one project report is required per group, but
must be completed as a group.
 For group project II, an in-class presentation is required as well. Project presentations will be
evaluated by the other teams as well as the instructor.
HOMEWORK: There will be 4 assignments during the term. The due dates for the assignments will be
announced.
GRADING: Your final grade will be determined based on your overall score out of 100.
 20% Homework
 30% Midterm
 20% Group project 1
 30% Group project 2
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MATH 372 — Mathematical Modeling I
Fall 2007
IMPORTANT DATES:
Wednesday, October 31, 2007 - Midterm
Friday, October 19, 2007 - Group Project 1 Reports Due
Wednesday, December 5, 2007 - Group Project 2 Reports Due
Wednesday, November 21 - Wednesday, December 5, 2007 – Project 2 Presentations
COMPUTER LABS:
Many assignment questions, and most likely your group projects too, require you to use computer packages,
in particular Maple, Excel or MatLab. If you have never used these computer packages, you undoubtedly will
encounter some frustrations, but they should not be a reason to despair. I will endeavor to provide as much
help with this as possible (for example, by providing sample programs/codes on the course website). A
MatLab tutorial will be arranged in September, 2007. If necessary, I am willing to schedule some
introductory tutorial sessions in Excel or Maple. You are not required to purchase the computer packages there are many computer labs on campus with the software installed.
COURSE PREREQUISITES: MATH 120 or 125 or equivalent, and MATH 215. Familiarity with
computing, differential equations, and probability will be helpful, but not required.
Policy about course outlines can be found in section 23.4(2) of the University Calendar.
The University of Alberta is committed to the highest standards of academic integrity and honesty. Students
are expected to be familiar with these standards regarding academic honesty and to uphold the policies of
the University in this respect. Students are particularly urged to familiarise themselves with the provisions of
the Code of Student Behaviour (online at http://www.ualberta.ca/secretariat/appeals.htm) and avoid any
behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts
and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or
expulsion from the University.
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