Applied decision methods

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Saint Leo University

GBA 334 Applied Decision Methods for Business

Course Description: This course explores the use of applied quantitative techniques to aid in business-oriented decision making. Emphasis is on problem identification and formulation with application of solution techniques and the interpretation of results. Included are probability theory; decision making under certainty, risk and uncertainty; utility theory; forecasting; inventory control; PERT/CPM; queuing theory; and linear programming. Prerequisite: MAT 201 Textbook: Saint Leo University. (2013), Quantitative analysis (custom). Boston, MA: Pearson Learning Solutions. eBook with print upgrade option – ISBN: 978-1-269-86314-8 You will access the eBook via a link in the Course Home menu, where you can purchase the print upgrade option. Software The use of statistical software is a required component in this course. It is expected that you already have a basic understanding of computers and Microsoft Excel. In-depth training is provided during the course on the appropriate use of the following packages:

 TreePlan-Student-179 Excel Add In

 Excel QM, version 4

 POM QM, version 4

 Analysis Tool Pack for Microsoft Excel must be activated To access the information needed to install the software, click the Software Installation Information link located under Resources in the course menu. Learning Outcomes: At the completion of the course you should be familiar with several decision methods of decision-making in a business environment. You will find that almost every type of problem to which you will be exposed in the business world has been explored and methods of solving them have been devised. You should be able to apply these methods to the real-world situations in which you will one day find yourself. The skills developed during this class include:

1. Explain the key attributes and differences between the normal, standard normal, and binomial distribution of variables.

2. Identify and explain the underlying assumptions, key variables, theoretical basis, and solution techniques for the following decision-making problems:

a. Decision Analysis b. Probability Theory and Analysis c. Regression Analysis d. Forecasting Methods e. Inventory Control Methods f. Project Management (including PERT/CPM) g. Network Models h. Queuing Theory i. Linear Programming Approaches and the Transportation and Assignment Special Cases j. Statistical Process Control

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3. Formulate and execute a solution to a variety of decision-making problems using computer software.

4. Identify, explain, and interpret the key areas of computer output for the various decision-making problems.

5. Apply one of the approaches covered in class to a real-world issue and present the findings. 6. VALUES OUTCOME: Demonstrate the core value of excellence by adequately preparing for

each class session, actively participating in class, and completing all required assignments. The focus of this course will not be on the development of the mathematical models used to analyze data. Instead the focus will be on the application and use of statistical methods. Each of the above outcomes will be accomplished through an examination of the following areas:

 What is the methodology? What questions does it answer?

 Define the problem. Develop the model. Determine what data is necessary.

 How do we analyze the data?

 What do the results look like?

 How do we interpret the results; i.e., what do the results mean? Core Value: The Management Department has identified excellence as the Saint Leo University core value of focus in this course. Excellence: Saint Leo University is an educational enterprise. All of us, individually and collectively, work hard to ensure that our students develop the character, learn the skills, and assimilate the knowledge essential to become morally responsible leaders. The success of our University depends upon a conscientious commitment to our mission, vision, and goals. Evaluation: Grades in this course will be based on the following:

Assignment Points Weight Discussions (8 at 25 points each) 200 20% Application Assignments (8 containing 28 total problems worth 10 points each) 280 28% Quizzes (4 at 30 points each) 120 12% Exams (2 at 100 points each) 200 20% Group Project 200 20%

Total 1,000 100% Discussions (20%): Discussion question responses are made in the Discussion Board for the appropriate module. To earn full credit, students must answer the question and make a proper citation for a reference which supports the answer. The instructor will not be grading on “volume,” but will instead be looking for discussions that answer the question and give a good description of all of the factors involved in arriving at that answer. A student asked to give an example from experience and has no relevant experience in that topic, should state he/she has no experience and then propose an example that he/she believes would be appropriate in answering the question. Review the guidelines posted for discussion question responses. Participation is integral to the discussion grade; this aspect will be graded based on your participation in the Discussion Board. As a general rule, each student is required to post thoughtful responses to at least two other students. In these responses, simply agreeing or disagreeing is unacceptable; students must also state the reason(s) for agreement or disagreement with the post. References that support the reasoning in the responses are also required.

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Application Assignments (28%): Application assignments require solving problems from the textbook. Students may use QM for Windows, Excel QM, or Excel to solve the problems. The answers must be submitted to the Dropbox in a Microsoft Word or Microsoft Excel file, depending upon the preference of the instructor. Students must state their answers within complete sentences so that understanding of applying the results of the computations can be observed by the instructor. Students should also include the work for all computations; this will assist in applying partial credit if student answers are not correct. Do not submit QM for Windows files as server security policies do not allow many of these files to be passed in the system. Additional details are provided in the modules. If showing the QM work is needed, either save as an Excel file (a function within QM) or paste screen captures of the QM Entry Screen before solving and the QM result screen(s). Quizzes (12%): Quizzes will consist of ten multiple choice questions with one hour to complete. Detailed instructions are provided in the modules. Exams (20%): The Midterm and Final Exams will each consist of 50 multiple-choice questions with four hours to complete. Detailed instructions are provided in the modules. Group Project (20%) The Decision Models term project is fairly flexible in terms of the types of projects that are acceptable. Each group may come up with its own project topic or choose from a list of topics in the Group Project Guidelines found in the course. In either case, the project topic must be approved by the instructor. Each group is expected to prepare a full report that addresses all areas noted in the guidelines. At the discretion of the instructor, this may include (a) make a short PowerPoint or Prezi presentation to the class reporting on their project (18 minutes including Q&A), or (b) writing a paper. Either way that is chosen, each group must submit files containing all of its project-related materials (e.g., Excel files, PowerPoint/Prezi presentation files, Word files, etc.). Additional details are provided in the course.

Grading Scale:

A 94-100 A- 90-93 B+ 87-89 B 84-86 B- 80-83 C+ 77-79 C 74-76 C- 70-73 D+ 67-69 D 60-66 F 0-59

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Course Schedule: Module 1 Introduction to Quantitative Analysis, Probability Concepts, and

Applications Objectives: When you complete this module, you should be able to:

 Apply mathematical modeling to solve business problems.  Solve to find the break-even point.  Apply basic probability analysis.  Calculate expected values and variance.  Solve problems using binomial, normal, exponential, and Poisson probability

distributions in Excel. Assignments:

Module 2 Decision Analysis Objectives: When you complete this module, you should be able to:

 Solve problems for decisions under uncertainty using maximax, maximin, and minimax regret techniques.

 Solve problems for decisions under risk using expected value.  Apply decision trees to graphically illustrate and solve decision analysis

problems.  Apply utility to determine decisions that result in the best outcomes.

Assignments:

Items to be Completed: Due No Later Than:

Post introduction to the class Thursday 11:59 PM EST/EDT

Read Chapters 1 and 2

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 1 Sunday 11:59 PM EST/EDT

Items to be Completed: Due No Later Than:

Read Chapter 3

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 2 Sunday 11:59 PM EST/EDT

Complete Quiz 1 Sunday 11:59 PM EST/EDT

Submit Group Project membership and topic Sunday 11:59 PM EST/EDT

Begin working on Group Project research proposal

Sunday 11:59 PM EST/EDT of Module 4

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Module 3 Regression and Forecasting Models Objectives: When you complete this module, you should be able to:

 Develop and solve simple linear regression equations from sample data and interpret the slope and intercept.

 Use correlation and coefficient of determination to determine the quality of fit for the regression line.

 Test the regression model for significance using the F distribution to determine if a relationship between x and y exists.

 Solve problems with several independent variables using multiple regression analysis.

 Apply appropriate types of forecasts and qualitative models to solve business problems.

 Use seasonal adjustment in forecasting.  Use the Analysis Add-In for Excel to solve a variety of regression and

forecasting problems. Assignments:

Module 4 Inventory Control Models Objectives: When you complete this module, you should be able to:

 Apply economic order quantity (EOQ) and related parameters to make decisions about how much stock to order.

 Determine the reorder point (ROP) to decide when to order stock.  Apply the production run model to build up stock levels as they are depleted.  Determine the appropriate level of safety stock to prevent stocking out of

product.  Solve problems using Excel QM

Assignments:

Items to be Completed: Due No Later Than:

Read Chapters 4 and 5

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 3 Sunday 11:59 PM EST/EDT

Complete Quiz 2 Sunday 11:59 PM EST/EDT

Items to be Completed: Due No Later Than:

Read “Inventory Control Models,” pages 197-227

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 4 Sunday 11:59 PM EST/EDT

Complete Midterm Exam Sunday 11:59 PM EST/EDT

Submit Group Project research proposal Sunday 11:59 PM EST/EDT

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Module 5 Project Management Objectives: When you complete this module, you should be able to:

 Apply PERT and CPM to plan, monitor, and control projects.  Determine critical path and project lengths.  Reduce the project time using project crashing.  Solve problems using Excel QM and POM QM software packages.

Assignments:

Module 6 Network Theory, Waiting Lines, and Queuing Theory Models Objectives: When you complete this module, you should be able to:

 Apply network theory to find the shortest route through a network, solve maximum flow problems, and find the shortest span to connect a network.

 Solve network problems both by hand and using POM QM.  Apply queuing system theory to solve business problems.  Solve queuing theory problems using Excel.

Assignments:

Items to be Completed: Due No Later Than:

Read Chapter 6

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 5 Sunday 11:59 PM EST/EDT

Complete Quiz 3 Sunday 11:59 PM EST/EDT

Items to be Completed: Due No Later Than:

Read Chapters 7 and 8

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 6 Sunday 11:59 PM EST/EDT

Complete Quiz 4 Sunday 11:59 PM EST/EDT

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Module 7 Linear Programming Objectives: When you complete this module, you should be able to:

 Apply the linear programming (LP) models to solve business problems.  Perform sensitivity analysis for LP problems.  Solve transportation, assignment, and facility location specific problems.  Solve linear programming problems using Excel.

Assignments:

Module 8 Statistical Process Control Objectives: When you complete this module, you should be able to:

 Define the quality of a product or service.  Develop four types of control charts: x-bar, R-bar, p, and c.  Understand the basic theory behind statistical quality control, including the

central limit theorem.  Determine whether or not a process is in control.

Assignments:

Items to be Completed: Due No Later Than:

Read Chapters 10 and 11

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 7 Sunday 11:59 PM EST/EDT

Submit Group Project final report Sunday 11:59 PM EST/EDT

Items to be Completed: Due No Later Than:

Read Chapter 12

View Audio Visual Presentation (AVP)

Post initial response to discussion question Thursday 11:59 PM EST/EDT

Post responses to at least two classmates Sunday 11:59 PM EST/EDT

Complete practice problems

Submit Application Assignment 8 Sunday 11:59 PM EST/EDT

Complete Final Exam Sunday 11:59 PM EST/EDT