MGS 3100 – Business Analysis [and Honors Business
Analysis]
Spring 2015 Syllabus
|
Instructor: Dr. Satish Nargundkar Office
Hours: By appointment |
Website: http://nargund.com/gsu E-Mail: snargundkar@gmail.com 12051 ALC 213 9:30
– 10:45 AM (Honors) |
Prerequisites:
·
Knowledge of
basic algebra (If you do not have the stated prerequisite, you should drop now
and attempt this course only after you have satisfied it.)
·
Proficiency in
Microsoft Excel®
Text:
1.
Business Analysis Exercises, by Nargundkar, S. & Samaddar, S., (Required
text) available at Alphagraphics,
34 Peachtree St., North of the Five Points intersection.
2. You may buy (optional text) a custom
book of selected chapters from the following online source: www.cengagebrain.com/micro/1-
Attendance/Class
Participation:
You are expected to
attend and meaningfully participate in all classes (who knows, you may actually
enjoy the class!) Assignments and projects remain due on the designated date
regardless of class attendance. If you do miss a class, you are responsible for
remaining current.
Honor Code:
It is more honorable to
get any grade with your own work than to get a better grade by using
someone else’s work as yours. While discussion with classmates is encouraged,
any work submitted must be your own (or your group’s, for group projects).
Evidence of plagiarism/cheating on an assignment/exam will result in a failing
grade for that assignment/exam, or even for the course.
Projects:
The projects and the
instructions for completing them will be discussed in class. Each project is a
group assignment. Students should organize themselves into groups of three soon
after the beginning of the semester.
Grading:
|
Activity |
Regular Section |
Honors Section |
|
Course Average |
Grade |
Course Average |
Grade |
|
Assignment |
5% |
5% |
|
94-96, 97+ |
A, A+ |
77-79 |
C+ |
|
Projects (2) |
25% |
20% |
|
90-93 |
A- |
73-76 |
C |
|
Tests (3) |
45% |
45% |
|
87-89 |
B+ |
70-72 |
C- |
|
Final Exam |
25% |
20% |
|
83-86 |
B |
60-69 |
D |
|
Mentor Paper |
N/A |
10% |
|
80-82 |
B- |
Less than 60 |
F |
|
Total |
100% |
100% |
|
|
|
|
|
Late projects will be
penalized at a rate of 5% per day. No
make up tests will be given. The final exam score will replace your worst test
score, unless the final exam score is lower.
Course
Assessment:
Your constructive assessment of this course plays an
indispensable role in shaping education at Georgia State. Upon completing the
course, please take the time to fill out the online course evaluation.
General Course
Objectives:
To demonstrate the application
of models in support of decision making in an enterprise, using some of the
most commonly used modeling approaches and principles. Upon completion of the
course, the student should:
1. Demonstrate competence in analysis/development of some
common models mathematically, graphically, and with a spreadsheet.
2. Be able to interpret model results in the context of
the business situation and explain them in plain language.
3. Demonstrate the ability to present information on a
simple web page.
Specific Course Objectives:
In
order to earn a grade of ‘A’ in the course, the student should, upon completion
of the course, be able to:
Overview:
1. Define basic modeling terms, including (but not limited
to) Physical model, Analog model, Symbolic model, Deterministic model,
Probabilistic model, Decision Variable, Random Variable, Parameter, Performance
Variable, Revenue, Fixed Cost, Variable Cost, Overhead Cost, Sunk Cost, Demand,
Price.
2. Explain the overview of the modeling process,
including types of models, data collection, analysis, and interpretation.
Profit Models and
Simulation
3. Analyze a business situation to identify revenues,
costs, and other parameters relevant to the modeling process.
4. Draw an influence diagram to map the relationships
between different variables of interest.
5. Build a basic profit model both with a spreadsheet and
without.
6. Perform breakeven analysis algebraically and
graphically, and with a spreadsheet.
7. Perform Crossover analysis algebraically and
graphically, both with a spreadsheet and without.
8. Interpret the results of Breakeven and Crossover
analyses.
9. Find the price that maximizes profit, given a demand
function, algebraically and graphically, both with a spreadsheet and without.
10. Compare and contrast Simulation with other types of
modeling.
11. Determine when simulation is an appropriate technique
to use.
12. Use random numbers from a random number table or a
spreadsheet function.
13. Construct cumulative probability distributions.
14. Simulate discrete (two valued or many valued) random
variables.
15. Graph the results of the simulations and interpret.
Time Series
Forecasting
16. Define the types of forecasting – Quantitative (causal
and time series) and Qualitative.
17. Forecast using the following methods for time-series
data (on a spreadsheet):
a. Naïve
b. Moving Averages
c. Simple Exponential Smoothing
d. Regression (Simple, Quadratic, Logarithmic)
e. Classical Decomposition (Trend and Seasonality)
18. Compute Bias, MAD (Mean Absolute Deviation), MAPE (Mean
Absolute Percentage Error), Standard Error, and R-Squared (for regression only)
for each of the forecasting methods.
19. Compare and contrast the different time-series
forecasting methods.
20. Interpret the results of the different forecasting
methods.
Decision Analysis
21. Differentiate between Decision making under ignorance,
risk, and certainty.
22. Define the terms Decision Alternative, States of
Nature, Payoff.
23. Compute payoff matrix for a given business scenario.
24. Define the criteria for choosing the best decision.
25. Determine the best decision using the MAXIMAX,
MAXIMIN, Laplace-Bayes, MINIMAX-Regret criteria.
26. Compute Expected Value (EV), EV under Perfect
Information (EVUPI), EV of Perfect Information (EVPI), Expected Opportunity Loss(EOL).
27. Explain why the minimum EOL is the same as EVPI.
28. Construct a decision tree.
29. Define decision nodes, chance nodes, branches,
payoffs, probabilities, pruning of branches.
30. Compute posterior probabilities using Bayes’ Theorem,
and incorporate them into analysis.
Honors Section
A
few extra topics will be discussed for the honors section. These can be seen in
the class schedule.
Accommodations for students with
disabilities
Georgia State University complies
with Section 504 of the Rehabilitation Act and the Americans with Disabilities
Act. Students with disabilities who seek academic accommodations must first
take appropriate documentation to the Office of Disability Services locate in
Suite 230 of the New Student Center.