Maryland in Europe

Course Number: MGMT 585

Course Texts:

Anderson, D.R., Sweeney, D. J., & Williams, T.A. (2001). 8th ed. Quantitative Methods for Business. St. Paul, MN: West Publishing Company.

Supplemental Material: Anderson, D. R., Sweeney, D. J., Williams, T. A., & Joseph, D.A. (2000). The Management Scientist. Version 5.0. St. Paul, MN: West Publishing Company.

Note: May be available from UM; if not, instructor may have available.

Credit Hours: Three (3)

Meetings: Term II 2000/2001 (21 Oct-10 Dec 2000)

Location: UM Heidelberg location, Germany

Classroom: TBA (Ask Field Rep)

Course Description: Acquaints students with the quantitative techniques commonly used in the decision making process. Topics include concepts of decision making and decision analysis, linear programming, sensitivity analysis, transportation and assignment problems, forecasting and time-series analysis, inventory concepts, PERT, and mathematical simulation. Prerequisite: MGMT 584.

Course Objectives: This course enables students to understand:

1. problem definition and orientation,

2. a structured approach to data analysis in

decision-making,

3. skills in model development, solutions, testing,

and validation,

4. business applications such as forecasting,

production scheduling, inventory control, capital budgeting,

plant location, quality control, and investment options, and

Teaching Method: This course will be conducted primarily through lecture, group work, and individual studies; however, personal communications through fax, phone, and other means may be used. Problem solving, student reports, and case analysis will be used to facilitate learning. Adjustments to the syllabus may be made as required, and notification will be made to students as soon as known. While statistics, per se, are complex, the major concern is to have each student understand what statistics are and how they can be used for business decisions. In this regard, students will review published research reports containing statistics and their application to business decision making and review videos involving application of various business statistical programs.

Class Policies: The main concern is communications! It is very important that you communicate any concerns to the instructor at the earliest. You will also be expected to read the assigned chapters, practice the problems, review the cases assigned, and complete all required work. The instructor reserves the right to alter the planned schedule when necessary for class benefit. Notice will be given prior to any changed requirement. Again, communications is the bottom line!

Participation: Student participation includes active communication, academic integrity, positive attitude towards learning, completion of assigned tasks, and communication. Case study analysis will be assigned as determined by the instructor based on chapter work. Each class session will be counted as one point, excluding the exams. Software programs may be used for chapter work; however, no software will be allowed for the exams.

Assignments: Each student will be assigned readings involving a business decision based on quantitative analysis, assigned case work, or a specific task. A student report of the analysis of the selected work will be required as established by the instructor.

Total point value will equal 20 points, as assigned by the instructor.

Examinations: A midterm examination will include course material learned to date. All exams will be open book, but will be time limited. The exams are valued at 33 points each. All student work must be shown on the exam to account for credit. Even though the right answer may not be given, credit for accurate work will be allowed. The exams may consist of short essays, multiple choice, and work problems. Some work problems may be partially answered: the student will be required to complete the answers.

The following class schedule will be general in nature in order to allow students to focus on the required material for each session. Students are required to read the assigned chapters for the week, review the end-of-chapter even numbered problems, accomplish the chapter self-tests, and answer specific odd-numbered problems. Case studies will also be assigned for specific classes. Changes may be made to adjust for the pace of the workload, depending on student knowledge and skills.

1. Comprehend the course objectives and learning outcomes.

2. Discuss business statistics and methodology.

3. Become familiar with key statistical terms.

4. Demonstrate knowledge through statistical work problems.

5. Explain probability concepts.

6. Discuss the concepts of probability distributions and random variables.

Provide a brief written biography of yourself to the instructor. Read Chapters 1 and 2 of the course text. Accomplish as many of the even numbered problems and the Self-Test items as possible using the end of text answer keys. Review the Management Scientist software package, if available. At the end of each chapter, review the Quantitative Methods in Practice case. This latter requirement applies to each chapter containing case work.

1. Determine optimal strategies through decision analysis.

2. Understand payoff tables and decision tree concepts.

3. Discuss the fundamentals of decision analysis.

4. Determine learning of topical items through practice exercises.

5. Determine between discrete and continuous random variables.

Read Chapters 1-4 of the course text and

practice work problems. Review the use of the Management

Scientist program. Complete any assigned taskings.

1. Discuss forecasting methods and techniques.
2. Summarize the components of time series forecasting.
3. Discuss forecasting as a planning tool.

Review previous work and read Chapters 1-6

of the course text. Complete any assigned taskings.

Objectives: Same as above plus complete final review of chapters 1-6.

Assignments: Read chapters 1-6 of the text. Use Management Scientist products for interpretations. Complete any assigned taskings. Prepare for the midterm (chs 1-6).

1. Discuss linear programming as a problem-solving approach to decision-making.
2. Understand the process in linear programming techniques.
3. Graph linear programming models.

Read chapters 7 & 8 of the course text. Practice chapter problems as above.

Read chapters 9 & 10 of the course text. Complete any assigned taskings.

1. Explain PERT/CPM.
2. Construct a project network.
3. Determine the probability of project completion times.
4. Demonstrate subject matter knowledge.

Read chapter 12 of the text and complete any assigned taskings.

1. Discuss topical issues relating to the text chapters.

2. Demonstrate quantitative report analysis.

3. Demonstrate understanding of research reporting and analysis.

Read chapters 1-18 of the course text and complete any assigned taskings.