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
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?