forecasting
Paper details:
ndividual Research Project: In this course, you will examine a problem or issue through the lens of Quantitative Analysis. This means that you must choose a project that is very specific, focused, and one on which you have a grasp of the inputs, process, and outputs. It would be beneficial if you could work with a specific issue in your workplace, as it moves the theory to practice, and you can improve your work life by applying the lessons from this course. You will work on the project throughout this course, help one another by discussing your ideas in the discussion forums, and hone your skill sets through collegial debate. Your paper will be approximately 10-20 pages in length, formatted in current APA format, include tables and/or figures, and have the following headings: • Introduction: A brief section that describes the symptom that you noticed, and provides readers with an understanding of the process. • Description of Problem: Developed through the Module 2 discussion forum. • Methodology: Developed through the Module 5 discussion forum. • Data collection: Developed through the Module 6 discussion forum. • Data Analysis: Developed through the Module 7 discussion forum. • Recommendations: Your interpretation of the analysis; provides readers with your ideas of your next logical steps. This could be a formal presentation to your boss, or perhaps a team meeting to highlight the issue, or so forth. This paper should be much like the case studies at the end of the textbook chapters. The introduction is the part of the case that is printed in the textbook. The remainder of the paper contains the details of how you collected the data and did the analysis. It will then end with the findings and recommendation. A writing template and writing resource videos are available in the online course. This assessment constitutes 15% of your final course grade. Note: When you submit your research project, it will automatically be submitted through an anti- plagiarism service called SafeAssign. SafeAssign checks all submitted papers against the following databases: • Internet – comprehensive index of documents available for public access on the Internet • ProQuest ABI/Inform database with over 1,100 publication titles and about 2.6 million articles from ’90s to present time, updated weekly (exclusive access) • Institutional document archives containing all papers submitted to SafeAssign by users in their respective institutions • Global Reference Database containing papers that were volunteered by students from client institutions to help prevent cross-institutional plagiarism.
This syllabus was developed for online learning by Dr. Wayne Harsha
MGMT_524_Online_Syllabus_01
1
5
Management Science
MGMT 524
EagleVision Home Blended
MMT
C
ourse
S
y
ll
abus
Credit Hours:
3 Credits
Academic Term:
AUG
1
0
201
5
–
OCT
1
1 201
5
Meetings:
Saturday, 11am EST
Location:
EagleVision Home
/
Blended
_______
Instructor:
Dr. Daniel Brandon
Office Hours:
Via Email, or via telephone 11am
–
5pm ET
Telephone:
901
–
737
–
1839
ERAU Email:
[email protected]
Required
Course Materials
:
Render, B., Stair, R. M., & Hanna, M. E. (20
1
5
).
Quantitative
analysis for management
(1
2
th ed.). Pearson/Prentice Hall.
ISBN:
978
–
0
–
13
350733
–
1
eText ISBN 10:
0133507483, ISBN 13: 9780133507485
Software: POM QM for Windows
or Excel QM (MAC)
This software comes with the textbook and should be
installed before
the course begins.
Page
2
of
8
American Psychological Association. (2010).
Publication manual of
the American Psychological Association
(6th ed.).
Washington, DC: Author.
ISBN: 978
–
1
–
4338
–
0561
–
5
(APA website:
http://www.apastyle.org/manual/index.aspx
)
Course Description:
In this course, students have the opportunity to gain knowledge and experience in the application of
management science processes and models used in
decision making in management.
Techniques include
decision theory, queuing theory, forecasting models, inve
ntory theory, linear and integer programming,
and network models including project management calculations (time
and cost) using PERT and CPM.
Computer techniques are used to solve problems and to communicate the results in a clear and
understandable fas
hi
on.
Emphasis is placed on using quantitatively bases analytical methodologies,
interpreting quantitative results, and communicating conclusions.
Prerequisites:
Satisfactory completion of Business Foundation Course MGMT 503D or
permission of the Graduate Pr
ogram Chair
.
Course
Goal
s:
This course
provides
the student with an opportunity to enhance his/her understanding of problem
–
solving, the Scientific Method, and Quantitative Analysis (QA); improve the individual’s ability and
skills to systematically analy
ze management problems, apply quantitative methods, and learn to use
Management Information Systems (MIS) and Decision Support Systems (DSS) to manage the
information resources necessary for resolving the problems and/or issues at hand.
Emphasis
is
on Q
uantitative Analysis (QA), the Scientific Method, and the skills and techniques for
determining the nature and identification of a problem and analyzing alternatives using quantitative
methods with particular interest and focus on current QA concepts, prac
tices, and applications; its very
important role in the support of management decisions; and its support, in turn, by DSS and
computerized MIS, particularly via software applications on the typical desktop personal/business
computers (PCs) of today.
Lear
ning Outcomes:
Upon
successful
course completion,
given a set of industry data or a case study scenario,
students will
be able to:
1.
Apply Quantitative Analysis and Management Science Techniques to model a variety of
Business problems and solve the resulting models using computer software. (MSM Program
Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 3)
2.
Utilize probability theory
to solve quantitative analysis problems. (MSM Program Outcome 1, 3,
& 7) (MBAA Program Outcome 3) (MSLSCM PO 2, 3, 4)
3.
Use Decision Theory to construct mathematical models useful in optimizing managerial
decisions. (MSM Program Outcome 1 3, & 7) (MBAA Pro
gram Outcome 1) (MSLSCM PO 3, 4)
Page
3
of
8
4.
Utilize moving averages, weighted moving averages, exponential smoothing and regression
analysis to develop appropriate forecasting models applying moving averages, exponential
smoothing, and time series models. (MSM Progr
am Outcome 1, 3, & 7) (MBAA Program
Outcome 3) (MSLSCM PO 2, 3, 4)
5.
Apply inventory planning and control models (e.g., EOQ, ABC Analysis, MRP, and JIT & ERP)
to maintain adequate inventory levels with an organization. (MSM Program Outcome 1, 3, & 7)
(MBAA
Program Outcome 3) (MSLSCM PO 1, 3, 4)
6.
Apply linear programming techniques to model, analyze, and solve a variety of managerial
Business and Aviation decision making problems. (MSM Program Outcome 1, 3, & 7) (MBAA
Program Outcome 3) (MSLSCM PO 3, 4)11
7.
Ap
ply the concepts of Project Management, including PERT/CPM, Transportation Models, and
Network Models, to calculate the probability of successful completion of a project. (MSM
Program Outcome 1, 3, 4, & 7) (MBAA Program Outcomes 2 & 4) (MSLSCM PO 3, 4)
8.
So
lve queuing theory problems from real world industry applications to evaluate cost and
effectiveness of service systems. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome
3) (MSLSCM PO 3, 4)
9.
Determine the most appropriate management science model and
apply that model to reach
optimized results and make a recommendation based on those computations. (MSM Program
Outcome 1, 3, 4, & 7) (MBAA Program Outcome 1) (MSLSCM PO 3, 4)
Grading
These are the major assignments in the course and will be the basis f
or evaluation according to the
grading scale shown in the table below.
Rubrics identifying the criteria by which your work will graded
are available in the Resources/Course Specific Resources area in your online course.
Course Grade Scale
Evaluation Items
& Weights
90
–
100%
A
Chapter Problems
20%
80
–
89%
B
Case Studies
20%
70
–
79%
C
Discussions
30%
50
–
69%
F
Capstone Case Study
15%
Individual Research Project
15%
Total
100%
Chapter Problems
:
In Modules 1
–
8, y
ou will solve s
pecific questions
from the end of the chapters
.
The purpose of this is to
allow you time to practice some of the key concepts in the chapters and
to
prepare you for the
Capstone
Case Study
.
There is no time limit to complete these,
but
you
are required to
turn in your answe
rs by the
end of each module
week
.
While many of the problems given in this course can be solved by the use of
Microsoft Excel,
all
of
the
problems assigned can be solved using the POM
–
QM program. In this course, POM
–
QM will be used
as
the default decision support software. This software
is available
as a
free
download
from the
textbook
publisher’s
companion website
.
Chapter problems constitute 20% of your final course grade.
