forecasting

forecasting Paper details: ndividual Research Project: In this course, you will examine a problem or issue through the lens of Quantitative Analysis. This means that you must choose a project that is very specific, focused, and one on which you have a grasp of the inputs, process, and outputs. It would be beneficial if you could work with a specific issue in your workplace, as it moves the theory to practice, and you can improve your work life by applying the lessons from this course. You will work on the project throughout this course, help one another by discussing your ideas in the discussion forums, and hone your skill sets through collegial debate. Your paper will be approximately 10-20 pages in length, formatted in current APA format, include tables and/or figures, and have the following headings: • Introduction: A brief section that describes the symptom that you noticed, and provides readers with an understanding of the process. • Description of Problem: Developed through the Module 2 discussion forum. • Methodology: Developed through the Module 5 discussion forum. • Data collection: Developed through the Module 6 discussion forum. • Data Analysis: Developed through the Module 7 discussion forum. • Recommendations: Your interpretation of the analysis; provides readers with your ideas of your next logical steps. This could be a formal presentation to your boss, or perhaps a team meeting to highlight the issue, or so forth. This paper should be much like the case studies at the end of the textbook chapters. The introduction is the part of the case that is printed in the textbook. The remainder of the paper contains the details of how you collected the data and did the analysis. It will then end with the findings and recommendation. A writing template and writing resource videos are available in the online course. This assessment constitutes 15% of your final course grade. Note: When you submit your research project, it will automatically be submitted through an anti- plagiarism service called SafeAssign. SafeAssign checks all submitted papers against the following databases: • Internet - comprehensive index of documents available for public access on the Internet • ProQuest ABI/Inform database with over 1,100 publication titles and about 2.6 million articles from '90s to present time, updated weekly (exclusive access) • Institutional document archives containing all papers submitted to SafeAssign by users in their respective institutions • Global Reference Database containing papers that were volunteered by students from client institutions to help prevent cross-institutional plagiarism. This syllabus was developed for online learning by Dr. Wayne Harsha MGMT_524_Online_Syllabus_01 1 5 Management Science MGMT 524 EagleVision Home Blended MMT C ourse S y ll abus Credit Hours: 3 Credits Academic Term: AUG 1 0 201 5 - OCT 1 1 201 5 Meetings: Saturday, 11am EST Location: EagleVision Home / Blended _______ Instructor: Dr. Daniel Brandon Office Hours: Via Email, or via telephone 11am – 5pm ET Telephone: 901 - 737 - 1839 ERAU Email: brandond@erau.edu Required Course Materials : Render, B., Stair, R. M., & Hanna, M. E. (20 1 5 ). Quantitative analysis for management (1 2 th ed.). Pearson/Prentice Hall. ISBN: 978 - 0 - 13 350733 - 1 eText ISBN 10: 0133507483, ISBN 13: 9780133507485 Software:  POM QM for Windows or Excel QM (MAC) This software comes with the textbook and should be installed before the course begins. Page 2 of 8 American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: Author. ISBN: 978 - 1 - 4338 - 0561 - 5 (APA website: http://www.apastyle.org/manual/index.aspx ) Course Description: In this course, students have the opportunity to gain knowledge and experience in the application of management science processes and models used in decision making in management. Techniques include decision theory, queuing theory, forecasting models, inve ntory theory, linear and integer programming, and network models including project management calculations (time and cost) using PERT and CPM. Computer techniques are used to solve problems and to communicate the results in a clear and understandable fas hi on. Emphasis is placed on using quantitatively bases analytical methodologies, interpreting quantitative results, and communicating conclusions. Prerequisites: Satisfactory completion of Business Foundation Course MGMT 503D or permission of the Graduate Pr ogram Chair . Course Goal s: This course provides the student with an opportunity to enhance his/her understanding of problem - solving, the Scientific Method, and Quantitative Analysis (QA); improve the individual's ability and skills to systematically analy ze management problems, apply quantitative methods, and learn to use Management Information Systems (MIS) and Decision Support Systems (DSS) to manage the information resources necessary for resolving the problems and/or issues at hand. Emphasis is on Q uantitative Analysis (QA), the Scientific Method, and the skills and techniques for determining the nature and identification of a problem and analyzing alternatives using quantitative methods with particular interest and focus on current QA concepts, prac tices, and applications; its very important role in the support of management decisions; and its support, in turn, by DSS and computerized MIS, particularly via software applications on the typical desktop personal/business computers (PCs) of today. Lear ning Outcomes: Upon successful course completion, given a set of industry data or a case study scenario, students will be able to: 1. Apply Quantitative Analysis and Management Science Techniques to model a variety of Business problems and solve the resulting models using computer software. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 3) 2. Utilize probability theory to solve quantitative analysis problems. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 2, 3, 4) 3. Use Decision Theory to construct mathematical models useful in optimizing managerial decisions. (MSM Program Outcome 1 3, & 7) (MBAA Pro gram Outcome 1) (MSLSCM PO 3, 4) Page 3 of 8 4. Utilize moving averages, weighted moving averages, exponential smoothing and regression analysis to develop appropriate forecasting models applying moving averages, exponential smoothing, and time series models. (MSM Progr am Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 2, 3, 4) 5. Apply inventory planning and control models (e.g., EOQ, ABC Analysis, MRP, and JIT & ERP) to maintain adequate inventory levels with an organization. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 1, 3, 4) 6. Apply linear programming techniques to model, analyze, and solve a variety of managerial Business and Aviation decision making problems. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 3, 4)11 7. Ap ply the concepts of Project Management, including PERT/CPM, Transportation Models, and Network Models, to calculate the probability of successful completion of a project. (MSM Program Outcome 1, 3, 4, & 7) (MBAA Program Outcomes 2 & 4) (MSLSCM PO 3, 4) 8. So lve queuing theory problems from real world industry applications to evaluate cost and effectiveness of service systems. (MSM Program Outcome 1, 3, & 7) (MBAA Program Outcome 3) (MSLSCM PO 3, 4) 9. Determine the most appropriate management science model and apply that model to reach optimized results and make a recommendation based on those computations. (MSM Program Outcome 1, 3, 4, & 7) (MBAA Program Outcome 1) (MSLSCM PO 3, 4) Grading These are the major assignments in the course and will be the basis f or evaluation according to the grading scale shown in the table below. Rubrics identifying the criteria by which your work will graded are available in the Resources/Course Specific Resources area in your online course. Course Grade Scale Evaluation Items & Weights 90 – 100% A Chapter Problems 20% 80 – 89% B Case Studies 20% 70 – 79% C Discussions 30% 50 – 69% F Capstone Case Study 15% Individual Research Project 15% Total 100% Chapter Problems : In Modules 1 - 8, y ou will solve s pecific questions from the end of the chapters . The purpose of this is to allow you time to practice some of the key concepts in the chapters and to prepare you for the Capstone Case Study . There is no time limit to complete these, but you are required to turn in your answe rs by the end of each module week . While many of the problems given in this course can be solved by the use of Microsoft Excel, all of the problems assigned can be solved using the POM - QM program. In this course, POM - QM will be used as the default decision support software. This software is available as a free download from the textbook publisher’s companion website . Chapter problems constitute 20% of your final course grade.