Taylor, B. M. (2010). Introduction to management science (10th ed.). Upper Saddle River, NJ: Pearson/Prentice Hall. QM for Windows and Treeplan add-on for Excel. This software is available in the Open Lab at Strayer campuses, and can also be downloaded from the textbook's companion website. http://wps.prenhall.com/bp_taylor_introms_10/112/28870/7390751.cw/index.html
Scientific Calculator INSTRUCTIONAL MATERIAL - Supporting The following resources provide additional background and supporting information for this course. There is no need to purchase these items for the course. Buglear, J. (2005) Quantitative methods for business: the A to Z. Oxford, U.K.: Elsevier Butterworth-Heinemann. Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Martin, R. K. (2010) Quantitative methods for business. (11th Ed.) Mason, OH: South-western (Cengage). http://www.msubillings.edu/BusinessFaculty/Harris/LP_Problem_intro.htm Dilgard, L. A. (2009, Summer) Worst forecasting practices in corporate America and their solutions -- case studies. Journal of Business Forecasting, 28 (2), 4 - 13. Retrieved from EBSCO-Host Business Premier database. Begley, S. (2004, April 23). Did You Hear the One About the Salesman Who Traveled Better? The Wall Street Journal (Eastern Edition), p. B.1. Retrieved from ProQuest National Newspapers Expanded database.
COURSE DESCRIPTION Applies quantitative methods to systems management (Decision Theory), and/or methods of decision-making with respect to sampling, organizing, and analyzing empirical data. MAT540 Student Version 1122 (11-29-2011) Final Page 1 of 19
COURSE OUTCOMES Upon the successful completion of this course, the student will be able to: 1. Describe the role of quantitative methods in business decision making. 2. Analyze decision-making problems electronically. 3. Create statistical analysis of simulation results. 4. Apply the most appropriate forecasting method for the properties of the available data. . 5. Solve linear programming problems. 6. Create sensitivity analysis on linear programming model parameters. 7. Apply linear programming models to project management applications. 8. Solve integer-programming problems. 9. Develop solutions for transshipment problems. 10. Use technology and information resources to research issues in Management Science 11. Communicate issues in Management Science.
COURSE EXPECTATIONS To obtain the most benefit from this class: Follow Strayer University’s policies and procedures as well as those specific to this class. o Class specific information can be found within the “Class Information” section within the Student Center. WEEKLY COURSE SCHEDULE The weekly schedule below describes the learning activities that will help you achieve the course outcomes listed above and the assignments that will be used to measure your mastery of the outcomes. Each week is divided into sections consisting of readings, lectures, activities and assignments. For selected assignments, you will find a rubric that will be used to evaluate your performance. Each week is divided into sections consisting of activities including readings, lectures and discussions, quizzes, and assignments. WEEK 1 Course outcome in focus: Describe the role of quantitative methods in business decision making. Use technology and information resources to research and communicate issues in Management Science. Supporting topics: Management science approach to problem solving MAT540 Student Version 1122 (11-29-2011) Final Page 2 of 19
Model building: break-even analysis Computer solution Management science modeling techniques Business usage of...