Dr. Aaron Ratcliffe
MBA 701 Syllabus
Spring 2015
MBA 701.01
QUANTITATIVE ANALYSIS
FOR DECISION MAKING
SPRING 2015:
Bryan 212
Mon. 6:30 – 9:20 PM.
DR. AARON H. RATCLIFFE
Office: Bryan 438
Phone: 336.256.8597
Office hours:
Schedule Appointment
*Email 3 preferred slots
Mon. – Fri.
1/12/15 to 4/27/15
E-mail: aaron.ratcliffe@uncg.edu
Walk-Ins:
Mon. 5:00-6:00 PM;
Tue. 1:00-2:00 PM
Wed. 3:30 PM – 4:30 PM
STUDENT LEARNING OBJECTIVES (SLOS)
This course develops quantitative methods and spreadsheet skills to support management
practice and decision making including: hypothesis testing, confidence intervals, regression
analysis, decision analysis, optimization and simulation modeling. The course goals are: 1)
Demonstrate the wide range of situations in which quantitative analysis improves decision
making and creates competitive advantages; 2) Develop students’ analytical thinking skills. 3)
Develop mastery of analysis using spreadsheet models, and effective communication of results.
Upon completing the course, the student should be able to:
1. Construct effective models of decision making situations using principles of
professional spreadsheet design.
2. Compute optimal solutions to decision making models for the management of a wide
range of situations in which quantitative analysis improves decision making.
3. Analyze spreadsheet simulation models and decisions with uncertain outcomes by using
multiple criteria for optimality and risk.
4. Describe a set of data using histograms, scatter diagrams and summary statistics.
5. Compute statistics from sample data to support confidence interval estimation,
hypothesis testing and regression analysis.
6. Infer the statistical precision of insights derived from confidence interval estimation,
hypothesis testing and regression analysis.
COURSE MATERIALS
REQUIRED
1) Laptop installed with MS Excel
2010 or later and add-ins: Solver,
Analysis Toolpak, and MegaStat.
Instructions on Canvas.
2) Course Pack. Digital and hard
copies available from Harvard
Business Publishing. See link on
Canvas. Includes online courses.
RECOMMENDED TEXTBOOKS
3) Essential Statistics in
5) Business Analytics:
Business and Economics. 2E Methods, Models, and
D. Doane and L. Seward.
Decisions. James R. Evans.
McGraw-Hill/Irwin. 2009.
Pearson. 2013.
4) Introduction to
6) Spreadsheet Modeling and
Management Science. 4E F. Applications: Essentials of
Hillier and M. Hillier. Irwin. Practical Management. C.
2010.
Albright and W. Winston.
MBA701, Spring 2015
Syllabus
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COURSE POLICIES
1. Course Format. This course meets for one semester of instruction with time devoted to
lecture, guided computing exercises, in-class lab assignments, and case discussion. Prior to
class, complete the assigned reading and exercises. The first part of the course on
management science covers decision making under constraints and decision making in the
presence of uncertainty (SLOs 1-3). The second part of the course on statistics covers
decision making utilizing information from data (SLOs 4-6).
2. Bring your laptop to every class to follow along with demonstrations and participate in lab
exercises. Bring case materials on days of case discussion. Tip: download all relevant files
before class so that you have them available regardless of the UNCG Network status.
3. Course Website. The course website is https://uncg.instructure.com/ (Canvas).
Announcements, slides, spreadsheets, supplementary notes, assignments and grades will be
posted to Canvas. Please confirm that you are receiving Canvas notifications in your inbox.
4. Non-class use of laptops, phones and tablets is prohibited and is a distraction for you and
those around you. Please step outside to handle any urgent emails or phone calls.
5. Graded Assignments. Your course grade is comprised of two exams, two problem sets, one
analysis project, two online tutorials, four case reports and case discussion according to the
following weights. If necessary, changes to due dates below will be updated via Canvas.
Management Science
Assignment
Due
3/16 6:30-7:30 PM (part 1),
MS Exam
3/19 at 9 AM (part 2)
Problem Set 1
2/12 at 9 AM
Problem Set 2
2/26 at 9 AM
Case Report 1
2/2 at 9 AM
Case Report 2
3/2 at 9 AM
Case Discussion
2/2 & 3/2
Online Course
1/29 at 9 AM
Total
Grand Total
Statistics
Weight
Assignment
Due
Weight
22%
6%
6%
4%
4%
3%
5%
50%
Stats Exam
5/4 7-10 PM
22%
Stats Project
4/16 at 9 AM
10%
Case Report 3
Case Report 4
Case Discussion
Online Course
4/20 at 9 AM
4/27 at 9 AM
4/20 & 4/27
4/9 at 9 AM
Total
4%
4%
3%
7%
50%
100%
6. Grading Criteria.
Your final course average will determine your minimum course grade according to the
following table. You may increase your course grade through good class participation.
Letter Grade
F
C C+ B- B B+ A- A
Minimum Numerical Score <68 68 78 80 82 88 90 94
MBA701, Spring 2015
Syllabus
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The following criteria will apply to the grading of assignments.
A: Work demonstrates clear understanding of the material under study, but also a
superior ability to utilize that material in the assignment. All criteria are met. Work goes
beyond the task and contains additional or outstanding features.
B: Work demonstrates a good understanding of the material under study, and utilizes the
material well in the assignment. The student meets the assignment criteria, with few
errors or omissions.
C: Work minimally demonstrates a basic or technical understanding of the material
under study, and uses some relevant material in the assignment. Work may not address
one or more criteria or may not accomplish what was asked.
F: Work that is incomplete, inappropriate and/or shows little or no comprehension of the
material under study.
7. Guidelines for Submitting Assignments. Completed assignments and exam files will be
uploaded to Canvas. Your grade will be based upon (1) how well you conduct your analysis
and (2) how professionally you communicate your results and ideas.
 Submit your assignments as one MS Word or PDF document and one Excel
workbook showing the steps of your analysis.
 The report should summarize the analysis of each problem or project part including a
brief overview of the task at hand.
 Reference in the body of your report the attached Excel workbook.
 Worksheets should be organized and annotated to readily communicate your results.
 Demonstrate clearly that you understand the principles and techniques being studied.
 Conclusions of the analysis should be explicitly stated. Briefly state the implications of
your analysis and answer any questions asked in the statement of the problem.
8. Exams. Exams will be given at the dates and times listed in the above schedule.
 The Management Science exam is given in two parts: Part 1 is a 60-minute online quiz to
be completed in class; Part 2 is a take home section to be submitted by the date above.
 The Statistics exam is given as a 3-hour in-class exam.
 Exams are open note, open book, open laptop, but no communication of any kind is
allowed, either verbal, written, or electronic except with the instructor. Cell phones must
be turned off and stowed away.
 You must notify the instructor at least 1 week prior if if you have a conflict for either
exam. Documented proof may be requested. For legitimate conflicts, a make-up exam
may be scheduled.
 Requests to correct grading errors must be made within one week of grades being
returned.
9. Optimization & Simulation Problem Sets. Details of the optimization and simulation problem
sets are provided in Canvas. You may work in 2-member teams for the problem sets, but
all students should individually attempt and comprehend all of the problems. Each team will
submit one report (MS Word or PDF) and one Excel workbook by the due date. Problem set
reports should include clear answers to each of the questions listed. Reference in the report
any work completed in an attached Excel file.
MBA701, Spring 2015
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10. Stock Project details are provided on Canvas. You will select a company and analyze the
performance of its common stock during the recent past. You may consult with others, but
each student must analyze a different stock and submit an individual assignment. Each
student will submit one report (MS Word or PDF) and one Excel workbook by the due date.
Project reports should begin with an executive summary of the key issues of the project, your
methodology, and your recommendations. Describe your assumptions, methods, and answers
to any project questions in the body of the report. Reference in the report any work
completed in an attached Excel file.
11. Online Tutorial Post-Tests: Two online tutorials must be completed as graded assignments:
1) Spreadsheet Modeling Online Course: Excel 2013 (or 2007); and 2) Quantitative Methods
Online Course. Both courses are available from Harvard Business Publishing and can be
accessed via course pack hyperlink available on Canvas. You are expected to complete the
tutorials individually. You may complete the tutorials at your own pace. The assessments are
not timed, but the results for the assessments must be submitted by the respective due dates.
You may refer to the tutorials and other notes while completing the assessments but you
are not to consult with others. Contact the instructor if you encounter technical issues
regarding the online tutorials.
12. Case Report assignments are posted on Canvas and must be submitted by the respective due
dates above. You may work in 3-member teams for the case project reports, but all
students should be individually prepared to discuss the case in class. Each team will
submit one report (MS Word or PDF) and one Excel workbook by the due date. Case reports
should begin with an executive summary of the key issues of the case, your methodology,
and your recommendations. Describe your assumptions, methods, and answers to any case
questions in the body of the report. Reference in the report any work completed in an
attached Excel file.
Self-evaluation and peer evaluations for case assignments will be required and an
individual’s grade may be penalized if there is sufficient evidence he/she has not taken
acceptable responsibility for the assignment or does not complete the evaluation. Case teams
should discuss expectations at the beginning of the semester. All team members should take
responsibility for making sure all parts of the assignment meet the agreed expectations.
13. Case Discussion and Class Participation includes being prepared for class, being involved in
class discussion, and being engaged with the material outside of class. You are expected to
be thoroughly prepared to discuss assigned readings and cases. You may be called upon at
any time to share your perspective, work with other students, or respond to a question. You
are encouraged to attend office hours and email the instructor with questions and insights.
Participation is essential because: 1) discussion about a business situation is most fruitful
with multiple perspectives; 2) articulating your thoughts and questions demands that you be
clear and precise; 3) it promotes critical thinking and maximizes your learning efficiency.
Effective communication and participation are vital business skills in any organization.
Participation in case discussion is an important part of your grade. The instructor assigns case
discussion grades based on the quantity and quality of your participation. The quality of
MBA701, Spring 2015
Syllabus
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participation is measured by how well you explain your own critical analysis, contribute
original ideas, make comparisons based on outside experience or readings, offer critical
questions for the class to consider, respond to questions raised by others, and offer feedback
to your teammates. If you plan to miss a case discussion, please notify the instructor one
week in advance so that an appropriate make-up assignment may be issued.
14. UNCG Academic Integrity Policy. You are expected to be familiar with and abide by the
UNCG Academic Integrity Policy. The Policy may be found at:
http://sa.uncg.edu/handbook/academic-integrity-policy/
On team assignments, each individual team members must take responsibility for all parts
of the assignment or face a potential penalty. On individual assignments, you are not to share
details of your work including computer files or printed output from your computer analysis.
Prohibited actions also include working together side-by-side on separate computers.
Specifically, on exams you are not to communicate with others in any way or share any of
the exam materials with others. Violations of the Code will result in penalties ranging from
an F on the assignment to an F in the course.
15. Bryan School Faculty Student Guidelines. The Bryan School faculty has approved a set of
guidelines for the conduct of classes. They can be found at the following link
http://bae.uncg.edu/wp-content/uploads/2012/08/faculty_student_guidelines.pdf
Be professional.
Have integrity.
Treat the classroom like a business meeting.
MBA701, Spring 2015
Class Schedule Detailed.
1/12
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***Tentative. Official schedule updated on Canvas.
Introduction to Optimization & Linear Programming: (SLOs 1 & 2)
1) What are optimization and linear programming? Why are they important?
2) Three components of every optimization model
3) Process & Guidelines for Professional Spreadsheet Design
4) Solve Linear Programs using Spreadsheets: the Solver Tool
5) Sensitivity analysis
6) Managerial problems where linear programming can be applied:
 Resource Allocation, Cost-Benefit Problems, Product-Mix Problems
In Class Examples
A2 Liquor
SoyBoy Farms
Pfizer Drug Company
Lab/Practice Exercises
ConZorro
Picasso Frames
National Credit Union
Prior to first class: 1) Update Canvas profile with picture and bio, 2) Install Solver,
Data Analysis Tool-Pak & MegaStat, 3) Complete Excel refresher and introductory
sections of Spreadsheet Modeling Online Course (up to “Importing Data Into Excel”)
Reference: Hiller & Hiller. Chapters 2-4.
1/26
Spreadsheet Modeling & Applications: (SLOs 1 & 2)
1) Assignment Problems
4) Debugging Spreadsheet Models
2) Scheduling Problems
3) Transportation Problems
In Class Examples
Midwest Financial
Keystone Police
Curly Crustaceans
Lab/Practice Exercises
Cargo Ships (Problem 3.33)
Staffing A Call Center (Case 2-3)
Medequip Company (Problem 3.16)
Spreadsheet Modeling Post Test due 1/29 at 9 AM
Reference: Hiller & Hiller. Chapters 2-4.
2/2
Linear Programming Case Discussion (SLOs 1 & 2)
1) Prudent Pensions (Case 4-1)
2) MacPherson Refrigeration Case (course pack)
In Class Examples
Prudent Pensions
MacPherson/Aggregate Plan
Case Report 1 due 2/2 at 9 AM
Reference: Hiller & Hiller. Chapters 2-4.
Lab/Practice Exercises
Investments Problem
Aggregate Planning Problem
MBA701, Spring 2015
2/9
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Decision Analysis: (SLOs 2 & 3)
1) Introduction to Probability & Random Variables
2) Three elements of a decision analysis. What are payoff tables?
3) Using decision trees to optimize decisions with uncertainty
4) Sensitivity Analysis: quantifying the value of information
5) How risk can affect the analysis: What is risk? Why is it important?
In Class Examples
Techware
Lab/Practice Exercises
SciTools
Better Banking or Bust
Optimization Problem Set due 2/12 at 9 AM
Reference: Online Tutorial. Class slides. Supplementary reading.
2/16
Introduction to Simulation (SLOs 1 & 3)
1) What is Monte Carlo simulation? Why is it important?
2) What are pseudorandom numbers? How do we generate and use them?
3) Statistical analysis of output
4) Optimization using the Data Table tool
5) How to measure risk in spreadsheet simulation models
6) How to balance multiple objectives under uncertainty
7) Managerial problems where linear programming can be applied:
a. Overage-Underage / Single-Period Inventory Models (Newsvendor)
b. Revenue Management
In Class Examples
Walton Bookstore
Bottle Company
Albatross Air
Lab/Practice Exercises
American Medical Association
Textbook
Harriet Hotel
Reference: Hillier & Hillier. Chapter 12, pp. 686-718.
2/23
Spreadsheet Simulation Models & Applications (SLOs 1 & 3)
1) Using Data Table to analyze multi-period models
2) Using spreadsheet templates to analyze simple queueing systems
In Class Examples
GF Auto
Rustbelt Maintenance
Lab/Practice Exercises
New Store
Hugh’s Repair Shop
Simulation Problem Set due 2/26 at 9 AM
Reference: Hillier & Hillier. Chapter 12, pp. 686-718.
MBA701, Spring 2015
3/2
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Simulation Case Discussion & Review (SLOs 1 & 3)
1) Merck & Company: Product KL-798
2) Risk Analysis for Merck and Company: Product KL-798
In Class Examples
Merck & Company
Lab/Practice Exercises
TRC Technologies
Case Report 2 due 3/2 at 9 AM
Reference: Hillier & Hillier. Chapter 12, pp. 686-718.
3/16
Management Science Exam
Part 1: 6:30 – 7:30 PM
Part 2: due 3/19 at 9 AM
Introduction to Statistics (SLOs 4 & 5)
1) What is statistics?
2) Collecting data: sampling concepts and methods
3) Describing data visually using Excel
4) Descriptive statistics: central tendency and dispersion of random quantities
In Class Examples
Stock Price
Surgical Recovery
Expense Ratio
Lab/Practice Exercises
Rice Krispies (4.39)
Ads as % of Sales (4.59 – Data Set A)
Airline Days (4.27)
Work corresponding sections of Online Tutorial
Reference: Doane & Seward. Chapters 1-4.
3/23
Sampling & Estimation: Confidence Intervals (SLOs 5 & 6)
1) The Normal probability distribution
2) The Central Limit Theorem
3) Properties of the sample mean
4) Estimating a confidence interval for the population mean or proportion
5) Selecting sample size to control confidence interval width
In Class Examples
Subway (7.57 and 7.74)
Chrysler MPG (8.39)
Ameritech Pages (8.38)
Lab/Practice Exercises
UVA Children’s & Procyon (7.65, 7.63)
Bushing Diameter (8.03)
SOX Requirements (8.48)
Work corresponding sections of Online Tutorial
Reference: Doane & Seward. Chapters 7-8.
MBA701, Spring 2015
3/30
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Hypothesis Testing (SLOs 5 & 6)
1) What are the steps in testing hypotheses?
I. State the null and alternative hypotheses
II. Specify the decision rule
III. Collect data
IV. Calculate the test statistic or p-value
V. Make decision
VI. Take action based on the decision
2) One-sample tests for the mean & proportion
3) Tests to compare two means or two proportions
In Class Examples
Noodles Service Times (9.61)
Single-Earner Mortgages (9.54)
Superintendent Salary (10.53)
Vail Ski Hats (10.57)
Lovastatin (10.44)
Lab/Practice Exercises
Beer Taste (9.64)
Cracked Eggs (9.66)
Shoe Size (10.06)
Home Value (10.61)
Debit Card Purchases (10.17)
Work corresponding sections of Online Tutorial
Reference: Doane & Seward. Chapters 9-10.
4/6
Regression: Estimating Relationships (SLOs 4, 5, & 6)
Least squares method: finding an equation to describe a linear relationship
I.
Prior to performing the regression
i. Is data cross-sectional or time series?
ii. Assess linear relationship. Scatterplots. Correlation matrix
iii. Model selection. Which explanatory variables to include?
iv. State a priori your hypotheses about signs of predictors
II.
Perform the regression.
i. Assess the goodness of fit of the model
ii. Assess overall model significance: F-Test. 𝑅 2 .
iii. How accurate is the model? Standard error and CoV
III.
Assess the significance of the drivers
i. Interpret p-values and confidence intervals for coefficients
IV.
Check the assumptions of your model
i. Multicollinearity: Correlation matrix and VIFs.
ii. Normality of residuals: outliers, skewness, Normal prob. plot.
iii. Heteroscedasticity:
iv. Autocorrelation for time series: Durbin Watson test.
V. Using the model for prediction
i. Write the estimated regression equation in standard form
ii. 95% prediction intervals for the model
iii. Validate the model using additional data
2) Binary predictors: dummy variables and categorical variables
3) Regression modeling techniques: using regression creatively
MBA701, Spring 2015
Syllabus
In Class Examples
Hybrid Sales
Salary Discrimination
P a g e | 10
Lab/Practice Exercises
HCS Financial Ratios
Portfolio Returns
Real Estate
Quantitative Analysis online post-test due 4/9 at 9 AM
Reference: Doane & Seward. Chapters 9-10.
4/13
Advanced Topics in Statistics & Lab Session
1) Time Series Analysis: Autocorrelation, Seasonality
2) Conjoint analysis
In Class Examples
Home Depot Revenues
Lab/Practice Exercises
See previous weeks
Statistics Stock Project due 4/16 at 9 AM
Reference: Doane & Seward. Chapters 1-4, 7-10, 12-13.
4/20
Statistics Case Discussion 1: (SLOs 4, 5, & 6)
3) Pedigree vs. Grit (Case) (course pack)
4) MBA Starting Salaries Case
In Class Examples
Pedigree vs. Grit
MBA Starting Salaries Case
Lab/Practice Exercises
Auto MPG
Case Report 3 due 4/20 at 9 AM
Reference: Doane & Seward. Chapters 1-4, 7-10, 12-13.
4/27
Statistics Case Discussion 2 & Review: (SLOs 4, 5, & 6)
1) Deconstructing the Price of Diamonds
2) Pilgrim Bank (A) Customer Profitability
In Class Examples
Price of Diamonds
Pilgrim Bank
Lab/Practice Exercises
Medical Office Value
Case Report 4 due 4/27 at 9 AM
Reference: Doane & Seward. Chapters 1-4, 7-10, 12-13.
5/4
STATISTICS EXAM
7-10 PM