Syllabus
| Mission Statement | Description | Objectives | Grading | Academic Integrity | Text |
School of Business Administration Mission
Statement:
"Committed to developing socially responsible leaders and
improving global business practice through innovative,
personalized education and applied research.”
This course examines how managers use data as the key input
for systematic business problem-solving. Topics include
collecting data, describing and presenting data, probability,
statistical inference, regression analysis, forecasting and risk
analysis. Extensive use of Excel for data analysis with a focus
on applied business decision-making. Common business processes
and business skills practiced are gathering and organizing data,
quantitative data analysis, forecasting, decision-making under
uncertainty and communicating or presenting results.
Prerequisite: GSBA 501 or GSBA 515 or concurrent.
The topics covered in this
class have direct application, as will be illustrated in the
examples used in class. They will also be
applied in future required classes such as GSBA 505 (Financial
Management and Analysis), GSBA 506 (Operations and the Global
Supply Chain), and GSBA 509 (Managerial Economics and Decision
Making), as well as the following electives:
- GSBA 528 (Business Cycles and
Forecasting)
- GSBA 550 (Marketing Research)
- GSBA
570 (Program/Project Management)
- GSBA 573 (Information Technology Project Management)
- GSBA 574 (Introduction to Electronic Commerce)
- GSBA 575
(Information Systems Analysis and Design).
Class interaction is welcome and encouraged, but the nature
of the subject means that there will be less discussion and more
lecture than in the other classes in
the MBA program.
At the completion of this course, students will be able to:
- find sources of data and understand the methodology of
their collection,
- apply the appropriate statistical techniques to
analyze data and interpret the results,
- use spreadsheet software to do statistical analysis and
present the results of the analysis, and
- recognize the ethical issues involved in the use and
misuse of statistical analysis.
Grades in this class will be based on
examinations (70%) and out-of-class assignments
(30%):
- There will be two tests during the
semester, each worth 35% of your grade. Each exam
will consist primarily of problem type
questions. Click here
to get an idea of what the exams will be
like. You may use your notes and book
during each exam. Make-up exams will be
given only if you have a written excuse.
- The two out-of-class assignments will allow
you to apply the concepts discussed in
class, using
spreadsheet software to do statistical
analysis. Although most of you will be familiar with the
use of Microsoft Excel, the text has a
supplemental section at the end of the
first chapter dealing with its use if you need a
refresher. The use of Excel is
integrated throughout the text.
Ethical behavior is expected at all times.
From the Graduate Bulletin: "Academic
dishonesty is an affront to the integrity of
scholarship at USD an a threat to the quality of
learning. . . Violations of academic integrity
include: a) unauthorized assistance on an
examination; b) falsification or invention of
data; c) unauthorized collaboration on an
academic exercise; d) plagiarism; e)
misappropriation of research materials; f) any
unauthorized access to an instructor's files or
computer account; or g) any other serious
violation of academic integrity as established by
the instructor. An act of dishonesty can lead to
penalties in a course such as reduction of grade;
withdrawal from the course; a requirement that
all or part of a course be retaken; and a
requirement that additional work be undertaken in
connection with the course."
 David M. Levine, David
Stephan, Timothy C. Krehbiel, and Mark L.
Berenson, Statistics for Managers Using
Microsoft Excel, 5th Edition, Prentice-Hall,
Inc., 2008.
The text comes with a CD-ROM that has a supplement to
Excel called PHStat2. While the supplement is not
required to complete this course, it helps
greatly in doing some of the required analysis.
|
