Instructor: Dr. Ken J. Kovach     Availability: 

            100 MSS               Phone: 01353 -860 671

            PSC 37, Box 3414     

            APO AE 09459          Email:

                                  INTERNET:KJKovach@cs.com

                                  Fax: +44 1353 860 671     

Course Text:

Anderson, D.R., Sweeney, D. J. & Williams, T.A.  (2001).

8th ed. Quantitative methods for business. St. Paul, MN: West Publishing Company. ISBN 0-324-02133

 

Supplemental Material-software: Anderson, D. R., Sweeney, D. J., Williams, T. A.; Joseph, D.A. (1999). The management scientist (5.0). St. Paul, MN: West Publishing Company.

Note: While the software is not required, it is a great opportunity to use current programs for the text problems and real-world applications.

 

Credit Hours: Three (3)

Meetings:  Term IV 2000/2001 (2 Apr - 20 Jul 2001)

Location: Distance Education. Participation at least three times a week will enable attendance requirements to be met.

 

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: PUAD 502 and either undergraduate statistics or 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    

     5. the use of statistics in business research.

 

Teaching Method:  This course will be conducted primarily

through distance education format, 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 in making business decisions.

 

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 requirement.  Again, communications is the bottom line! Incompletes are not automatic. Students having good reason to extend the course (personal leave, vacations, and so forth are not good reasons) may request an extension to the instructor prior to the end of the course. Incompletes will not be assigned after the course is over.

 

Grading:

  Participation      -  50 points   A = 90 -100 points

  Midterm exam       -  25  "       B = 80 - 89  "

                                       C = 70 - 79  "

  Final exam         -  25  "       F = below 70 "

               Total - 100 points

 

Participation: Student participation includes active communication, positive attitude towards learning, completion of assigned tasks, and communication.  Case study analysis will assigned by the instructor. Software programs may be used for chapter work; however, no software will be allowed for the exams. For each week readings, problem work, case work, and other taskings have been identified in the course schedule. Due dates for individual work are also established. Participation points will be assessed based on active participation and submission of reports on time. Conference input discussions will be required as part of participation. Study groups may also be assigned. Due dates for required inputs will be identified and also indicated in the course schedule. Quality of responses will be assessed subjectively by the instructor, but length, depth, and presentation of all responses will always be considered. Total value = 50 points.

 

Examinations:  A midterm examination will include course material involving Chapters 1 thru 6. The exam will be an open book exam, valued at 25 points. UM policies identify on-line examinations with 48-hour windows: this will be followed as closely as possible. Make-up exams will also be on-line.  Student work should be shown on the exam to account for full credit. Even though the right answer may not be given, credit for accurate work will be allowed. A final exam (Chapters 7, 8, 9, 10, 12, and 13) will be similarly applied (25 points). The exams will consist of short essays and work problems. Some work problems may be partially answered: the student will be required to complete the answers. The midterm will be in the 8^th week of the course (18-25 May) and the final exam will be in the final week (13-20 July).

 

 

Course Schedule

 

The following class schedule will be general in nature in order to allow you to focus on the required material for each session. You are required to read the assigned chapters for the week, review the end-of-chapter even numbered problems and chapter self-tests, and answer specific odd-numbered problems. Note: Review the Appendices in the text for self-test and even-numbered correct answers. Case studies will also be assigned for specific classes.

 

 

Week      Session Dates        Assignments

1 & 2     2 Apr-15 Apr        Read Introduction and review all

                         course materials.

Review the Management Scientist      

program and pages 24-26 of the text.

Read Ch 1 (course text).

Practice the even-numbered problems  

and Self-Test items-answers in the 

back of the text.

Provide a brief bio of yourself (due 

9 Apr)as Conference 1.

Work Ch 1 problems 1, 3, 5, 7, 13, 

& 17 and submit answers to the Assignments area. Do this procedure for all work problems.

                         Submit answers to Assignments nlt 16  

                         Apr 2001.

Go to the Conference area and submit input to Conference 2 – due 16 Apr.

Review any powerpoint files received.

Objectives:

1.  Comprehend the course objectives and learning outcomes.

2.  Discuss research hypothesis and methodology.

3.  Become familiar with key statistical terms.

4.  Demonstrate knowledge through assigned work problems.

5.  Understand the course requirements.

6.  Demonstrate knowledge through completion of taskings.

 

3 & 4     16 Apr – 29 Apr Read Chapters 2 & 3 (text).

Practice even-numbered problems and 

                         the Self-Tests.

Work Ch 2 problems 3, 5, 9, 11, & 15:

                         due 30 Apr.

Work Ch 3 problems 5, 7, 11, 19,

& 25: due 30 Apr.

Complete Conferences 3, 4, & 5-due 26

Apr.

Review powerpoint presentation files

received.

Objectives:

1.  Explain probability concepts.

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

3.  Demonstrate subject knowledge by problem completion.

4.  Develop review and application techniques.

5 & 6      30 Apr – 13 May  Read Chapters 4 & 5.

Practice even-numbered problems and  Self-Tests.

Work Ch 4 problems 9, 13, 21, & 23: due 14 May.

Work Ch 5 problems 3 & 9: due 14  May.

                              Complete Conferences 6 and 7: due

   7 May

Objectives:

1.  Determine optimal strategies through decision analysis.

2.  Understand payoff tables and decision tree concepts.

3.  Discuss the fundamentals of decision analysis.

4.  Demonstrate group communications.

 

 

7 & 8        14 May – 25 May  Read Ch 6.

Practice even-numbered problems and Self-Tests.

Work Ch 6 problems 3, 7, 15, 17, & 27: due 25 May.

Conferences 8 & 9: due 18 May.

Objectives:

1.  Discuss forecasting methods and techniques.

2.  Summarize the components of time series forecasting.

3.  Demonstrate knowledge of the subject through assessment.

 

8         20-26 May 2001        Midterm examination!

 

This will be an on-line examination with a 48-hour window. Material will consist of Chapters 1 through 6.

 

9 & 10        27 May – 9 Jun  Read Ch 7.

Practice even-numbered problems and Self-Tests.

Work Ch 7 problems 3, 15, 21, 23: due 9 Jun.

                                Conferences 10 and 11 due 4 Jun.

Objectives:

1.  Show linear programming graphical methods.

2.  Demonstrate knowledge of linear programming techniques.

 

 

11 & 12       10 Jun – 23 Jun  Read Chs 8 &9.

Practice even-numbered problems and Self-Tests.

Work Ch 8 problems 3 and15:due 

22 Jun.

Work Ch 9 problems 3, & 11: due 22 Jun.

Conferences 12 and 13 due 22 

Jun.

 

 

 

Objectives:

1. Understand linear programming applications.

2. Develop linear programming solutions through applications.

3. Obtain practice and experience in formulating realistic linear programming models.

 

 

13 & 14     24 Jun – 8 Jul  Read Chs 10 and 12.

Practice even-numbered problems and Self-Tests.

Work Ch 10 problems 3, 5, 7 and 15: Due 9 Jul.

Work Ch 12 problems 7, 15, & 19: due 9 Jul.

                                Conferences 14 & 15 due 6 Jul.

Objectives:

1. Identify special features of the transportation problem.

2. Become familiar with the types of problems that can be solved with transportation models.

3. Demonstrate application of transportation models.

4. Understand the role and application of PERT/CPM.

5. Demonstrate completion of critical path and project completion time.

 

15 & 16   9 Jul – 20 Jul         Read Ch 13 and review practice

and self-test problems.

Work problems 9 and 19:due 20 Jul.

Complete Final Exam: due 20 Jul.

Complete all remaining tasks required.

                                Conferences 16 & 17 due 19 Jul.

 

Objectives:

1.     Discuss inventory models for independent demand.

2.     Determine optimal solution of inventory ordering.

3.     Complete all course work.

4.     Assess student knowledge and performance.

Instructor Bio

    Ken J. Kovach is a faculty member for the University of Maryland since 1993 and also has taught research, statistics, and managerial courses for several other universities. Since 1981, he has taught 400+ graduate/undergrad courses in a variety of subjects. Ken previously served 23 years in the U.S. Air Force, first enlisted and then commissioned, in logistics, plans, transportation management, aerial delivery, command staff, and airborne command positions.

    Within distance education, he has continually taught over the internet since 1995 after developing three university programs for Embry-Riddle and one business management certificate program. He has developed research guidelines for various universities and serves mainly as the chair on graduate research project committees. Ken is active in various professional associations, to include the American Counseling Association, American Statistical Association, and Transportation Administration. His recent publication was Corporate Aviation Management. 

    Ken's bachelor of science was from the University of Tennessee in business, master of arts in guidance and counseling from Wayne State University, and doctorate in higher education from Nova University. He has a British wife, Sally, and two daughters, Katie and Chris.