Lundquist College of Business

Fall 2004

Welcome | Syllabus | Announcements | Assignments | Handouts | Data


DSC 410/510, 8:00-9:50am Tuesday/Thursday, 312 Lillis
Instructor: Iain Pardoe, 474 Lillis (346-3250), e-mail: ipardoe at

Why Learn About Multivariate Statistical Methods?

In order to make informed decisions, business decision-makers need to identify and quantify relationships between multiple information sources that are usually interrelated. Inflation, for instance, is related to taxes, interest rates, the money supply, oil prices, the business cycle, foreign wars, and a good deal more. Buyers' reactions to an advertisement may be related to the price of the item, competitors, warranty terms, previous experiences with the product, conversations with neighbors, and season of the year. A complete system of complicated relationships can exist in any single problem, with decisions affected by many variables that all interact with one another.

In striving to make some sense out of our environment, to seek some order to the chaos of inter-relationships, there are many approaches, including intuition, logical reasoning, and making simplifying assumptions. This course instead relies on the accepted framework of modern multivariate analysis techniques as it applies to business decisions. In particular, we consider conjoint analysis, cluster analysis, discriminant analysis, logistic regression, multidimensional scaling, correspondence analysis, and discrete choice analysis; all can be very powerful means of achieving parsimonious descriptions, explanations, and predictions of reality.

Office Hours

Tuesday 4-5pm Also by appointment
if you cannot make
any of these times
Wednesday 12-2pm
Thursday 4-5pm

Required Text

"Multivariate Data Analysis" (1998, 5th edition) by Hair, Anderson, Tatham, Black. The book is available from the University Bookstore on 13th and Kincaid for about $114, or you could try getting the much cheaper black and white paperback "international edition" from the "used & new" link on

Course Outline

The tentative course outline is as follows:

Week Date Class Topics
1 U 9/28 1. Introduction to course and examining your data
H 9/30 2.
2 U 10/5 3. Conjoint analysis
H 10/7 4.
3 U 10/12 5.
H 10/14 6.
4 U 10/19 7. Cluster analysis
H 10/21 8.
5 U 10/26 9.
H 10/28 10. Discriminant analysis and logistic regression
6 U 11/2 11.
H 11/4 12.
7 U 11/9 13.
H 11/11 14. Multidimensional scaling and correspondence analysis
8 U 11/16 15.
H 11/18 16.
9 U 11/23 17.
H 11/25 - Thanksgiving Holiday - no class
10 U 11/30 18. Discrete choice analysis
H 12/2 19.
11 U 12/7 - Final exam at 8:00 am


Computing is an integral part of this course. We'll use "Microsoft Excel" as well as "SAS" statistical software. No prior knowledge of SAS is expected, and the software is installed on the computers in the LCB Business Technology Center. Information on the use of the Business Technology Center is available at You can also obtain a copy of SAS for use on your own computer from the University Computer Center - see

You will receive instruction on software use during the lectures. Information on the use of SAS is also available from the software help itself. All data-sets discussed in the text and to be used in the course are available at the course web-site (see below). There will also be handouts on the software at this web-site.


You are expected to attend all lectures, to prepare for examples that we'll do in class, to keep up with assigned reading of the text, to self-test your understanding of the material, to complete one (undergraduates) or two (graduates) projects, and (optionally) to take a final exam.

Class time will be spent discussing various multivariate statistical techniques (see "Course Outline" above), with emphasis on demonstrating how to use the techniques with real data. Some of the real data that we'll use will come from you, so you'll be asked to prepare for some lectures by obtaining data that we'll then analyze in class. Somewhere in the region of 30 to 35 pages of reading from the text-book will be assigned per week. This may be supplemented with other sources of material.

Graded homework is a required part of this course, and will be entirely e-mail based. Also, questions to self-test your understanding of the material covered will be assigned, and suggested solutions will be provided to allow you to check your answers. Preparing for class (by, for example, obtaining some data) and class attendance will form part of your grade. Finally, there will be one or two projects based on analyzing data that you obtain. (Undergraduates are only required to do one project, while graduate students need to do two.) You can do the projects by yourself or in a group of up to four. For those doing project-work in groups, each member of the group contributing to the project gets the same score; if you don't contribute to your group's project you get zero.

There is no mid-term exam, but there is an optional final exam for those wanting an "A" from the class (see "Grading" below). The final exam is scheduled for 8:00-10:00am Tuesday, December 7; this will be comprehensive and so cover everything from the term.


The class will be graded on the A-F scale using the following guidelines:

Graduate students: Undergraduates:
Homework, class preparation, attendance: 200 Homework, class preparation, attendance: 300
Project 1: 250 Project: 400
Project 2: 250
Comprehensive final exam: 300 Comprehensive final exam: 300

To get a "B" you'll have to score about 670 points, while a "B+" will require about 800 points, an "A-" will require about 870 points, and an "A" will require about 930 points. Anything less than 500 will get a "C" or worse. Note that an unsatisfactory project (or failing to do a required project) will score minus 100 points so that it is not possible for graduate students to get a "B" with just one satisfactory project, or for undergraduates to get a "C" without a satisfactory project.


The web-site for this course is at There you will find course announcements, assignments, copies of handouts, and data used in class.

Charles H. Lundquist College of Business
Code of Professional Business Conduct

A Statement of Values
The Lundquist College of Business learning community is committed to a set of core values that guide our interactions with one another. Our values are as important within our LCB community as within the business community. Our values help define both how we aspire to act and what it means to be a business professional.
Members of our community act with integrity and honesty. These qualities are essential in providing a basis for trust and go to the core of what is expected from business professionals.
Our community conveys respect for the dignity of all people. Our relationships are based on mutual respect. Differences of opinion are discussed openly and civilly. These discussions focus on issues and are presented in a courteous manner. We are sensitive to the impacts of both our words and actions on others.
We encourage all members of our community to exchange ideas freely within the bounds of reasonable behavior. We recognize that learning requires an open environment.
We act publicly and accept responsibility for our actions. We understand that the community will keep us accountable for our dealings. We deliver on the commitments and promises we make to others.
Our community is stronger when we work as a team. We foster attitudes encouraging members of the community to give and receive constructive criticism, and develop creative solutions to challenges.

Disability access statement

The University of Oregon is an equal opportunity, affirmative action institution committed to cultural diversity and compliance with the Americans with Disabilities Act. If you have a documented disability and anticipate needing accommodations in this course, please make arrangements to meet with the instructor soon. Please request that the Counselor for Students with Disabilities send a letter verifying your disability. This syllabus will be made available in alternative formats upon request.

Welcome | Syllabus | Announcements | Assignments | Handouts | Data
© 2004, Iain Pardoe, Lundquist College of Business, University of Oregon
Last updated September 20, 2004

The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the University of Oregon.

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