Introduction to Interdisciplinary Consulting
Fall 2003 - Matthias K. Gobbert and Nagaraj K. Neerchal
Section 0101 - Schedule Number 7730/7731
This page can be reached via the homepage
of the Scientific Computing and Statistical Data Analysis Lab at
Consulting Projects and Class Presentations
The class presentations of the consulting projects will be held on
Tuesday, December 02, 2003 and Thursday, December 04, 2003
starting at 10:00 a.m. in MP 401.
Please follow the link to the Program
for the titles and abstracts.
Scores and grades will be posted here at the end of the semester.
- For Mathematics projects:
Matthias K. Gobbert, Associate Professor of Mathematics,
Math/Psyc 416, (410) 455-2404, email@example.com,
office hours: MW 03:00-04:00 or by appointment
- For Statistics projects:
Nagaraj K. Neerchal, Professor of Statistics,
Math/Psyc 437, (410) 455-2437, firstname.lastname@example.org,
office hours: MW 11:45-12:45 or by appointment
- Time and Room: TTh 10:00-11:15, MP 401;
see the Course Description below and the
for more information.
- for Math 750:
Math 620, Math 630, Math 650,
familiarity with Matlab,
or instructor approval.
- for Stat 750:
Stat 601, Stat 602, Stat 651, Stat 653,
familiarity with SAS and Splus,
or instructor approval.
- The following books are recommended references on various topics:
For additional recommendations on various topics
including Unix/Linux and parallel programming, see
- Recommended books on the techniques of consulting,
both mathematical and statistical:
We will discuss selected parts of both books in class.
- James R. Boen and Douglas A. Zahn,
The Human Side of Statistical Consulting,
Lifetime Learning Publications, 1982.
A newer edition of this book may be available.
- Javier Cabrera and Andrew McDougall,
- D.J. Hand and B.S. Everitt, Editors,
The Statistical Consultant in Action,
Cambridge University Press, 1987.
- Recommended book on Matlab:
- Recommended books on SAS:
- Lora D. Delwiche and Susan J. Slaughter,
The Little SAS Book: A Primer,
second edition, SAS Publishing, 1998.
- Art Carpenter,
Carpenter's Complete Guide to the SAS Macro Language,
SAS Publishing, 1998.
- Recommended book on Splus:
- William N. Venables and Brian D. Ripley,
- Grading policy:
- First Quarter of the Semester: Small Individual Project
Effective Independent Research and Oral Communication Skills
Total score for the first quarter of the semester: 25%
- Oral presentation (formal and content): 15%
The assignment consists of learning a significant useful
tool in Mathematics or Statistics within one week and
introducing it to the other students in class
in a 30-minute demonstration. The other students should be
able to use and apply that tool as the outcome of the presentation.
- Submit feedback to every presenter: 5%
Each member of the audience will provide written feedback
to the presenter about the presentation both with respect
to form and content.
Being able to give useful, critical, but also encouraging
feedback is an important skill to learn.
The facilitators will collect and
review the audience feedback before giving it to the presenter.
- Creation of a homepage: 5%
Every student will create a professional homepage that can
be used throughout the semester and beyond for communication.
- Second Quarter of the Semester: Small Team Project
Effective Team Work and Written Communication Skills
Total score for the second quarter of the semester: 25%
- Deliverables including written report
(formal and content): 20%
Teams of two or three students will be assigned a small project
with concrete deliverables that need to be submitted
along with a written report.
Strageties for effective team work will be discussed in class
to back up your experience.
This project will provide invaluable experience for
working effectively in a team. Demonstrated experience of
team work is a useful marketable skill.
- Peer review of other team's written report: 5%
Each student will review in writing another team's report
for content, clarity, and presentation.
Again, it is important to learn
how to give appropriate, critical, candid feedback.
In turn, every team will be able to learn from the two or more
reviews it will receive.
- Second Half of the Semester: Consulting Project
Learning Goals: Putting all Skills Together!
Total score for the second half of the semester: 50%
At the end of the consulting project, the facilitator will
solicit feedback from the client on the experience.
The grade will be assigned solely by the facilitator.
- Client-focused activities and content:
The consulting project in the second half of the semester
will provide the opportunity to put all skills together
by working with a client from outside the department.
Your responsibility will be to interview the client about his/her
needs, maintain regular contacts with the client, and to deliver
the agreed-upon deliverables; these might include a written report,
computer code, graphics, and/or presentations
to the client's organization.
The background research includes learning the client's language,
learning about the problem, and stating the problem yourself.
If the size of a project warrants it, a team of students
may be assigned to it.
All aspects of the consulting will be supervised by one of the
instructors of this course as facilitator.
- Background research: 15%
- Quality of the deliverables: 15%
- Class-related efforts:
- Professional behavior: 5%
This includes timeliness in client contact,
appropriateness of updates to the client, etc.
- A chronogical journal: 5%
You are required to maintain a detailed and dated journal
of all consulting-related activities.
- Regular updates to the facilitator: 5%
Each student will give regular updates to the facilitator
in class on the progress of the project. These progress
reports are an excellent opportunity to ask the audience
for feedback on your approach!
- Oral presentation: 5%
At the end of the semester, every student will present the
results of his or her consulting project to the class
along with a review of the experience.
This course provides an introduction to professional consulting
in mathematics and statistics.
Typical consulting activities include the following elements:
We are planning to invite people from across the campus and from
local companies and government agencies
to be clients to provide real-life consulting experience.
Expect to collaborate in teams of Mathematics and Statistics students,
if appropriate to the project and the client.
- Get information on the project from the client
and help to formulate the problem in the client's language.
- Translate the problem into the language of mathematics or statistics.
- Solve the problem efficiently and appropriately using any tools
at your disposal.
- Deliver the product to the client, which may consist of
a written report, an oral presentation, computer code,
and/or training services.
Students will gain experience in approaching application problems and
gain confidence in their ability to apply their mathematical and
statistical tools. Through the regular reports to the class,
students will greatly improve their oral presentation and writing skills.
The course is designed with non-academic consulting in mind, but the
same skills are invaluable also for students desiring academic employment.
One of the many other benefits of the class include contact with
clients for possible research or internship opportunities.
The course will begin with presentations by students on various
tools and techniques. For instance, advanced features of software tools
or analytical techniques may be presented to the class.
In the second phase,
the facilitators will assign small projects to teams of students.
The second half of the semester will feature a larger
consulting project working with a clients from outside of the department.
The deliverables of the consulting projects will be determined by the
client and might consist of a written report, computer code,
associated documentation, and/or training in its use.
In addition to the product delivered to the client,
each team will document its consulting activities to the class
in an oral presentation and a brief written report that outlines
and explains the methods and tools used in the project.
Mathematics students should register for Math 750,
Statistics students for Stat 750.
The students in this class should have background in the relevant
first-year graduate courses in mathematics or statistics, respectively.
The ability to use one or more professional software package effectively
Students should be ready to learn more in their own fields
as well as be exposed to new tools and methods by interacting
with their classmates.
If you are interested in this course as a student or
if you have a project to present as a potential client,
please contact any of the facilitators.
Information for Download
Instructions: Open the file by clicking on the link; plain text
should appear in your browser window. Then use the "File -> Save As"
functionality of your browser to save the data to a file.
The details may vary depending on your browser software and operating
system. Contact me if there is a persisting problem.
UMBC Academic Integrity Policy
By enrolling in this course, each student assumes the responsibilities of
an active participant in UMBC's scholarly community in which everyone's
academic work and behavior are held to the highest standards of honesty.
Cheating, fabrication, plagiarism, and helping others to commit these acts
are all forms of academic dishonesty, and they are wrong. Academic
misconduct could result in disciplinary action that may include, but is
not limited to, suspension or dismissal.
To read the full Student Academic Conduct Policy, consult the
UMBC Student Handbook, the Faculty Handbook,
the UMBC Policies section of the UMBC Directory for undergraduate students,
or the Graduate School website for graduate students.
Copyright © 2003 by Matthias K. Gobbert and Nagaraj K. Neerchal.
All Rights Reserved.
This page version 4.2, November 2003.