Course Code & Number
IE 444
Course Title
Forecasting Methods
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 5 ECTS Credits
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite::
Pre-requisites: MATH 232
Co-requisites: NONE
Catalog Description
Statistical forecasting methods. Time series decomposition. Regression. Exponential smoothing. Box-Jenkins ARIMA models.
Course Objectives
The course aims to teach forecasting techniques for manufacturing and service operations. The techniques include time series decomposition, regression methods, smoothing techniques, regression methods, exponential smoothing and Box-Jenkins ARIMA models. Ultimate goal is to teach techniques for comparing individual methodologies, selecting a methodology and designing a forecasting system for a given organization.
Course Learning Outcomes
Upon succesful completion of this course, a student will be able to
1. Apply basic techniques of data analysis and forecasting [a2] [B3]
2. Distinguish between short-term andlong-term forecasting (B4, a2)
3. Compare individual forecasting methodologies(B6, c)
4. Choose and defend the most appropriate forecasting methodin different situations. (B6, c)
5. Designa forecasting system for a given organization(B5, c)
6. Evaluate the performance of forecasting methods (B6, b2,h)
Learning Activities and Teaching Methods:
Telling/Explaining
Discussion/Debate
Reading
Problem Solving
Case Study/Scenarion Analysis
Assessment Methods and Criteria:
Test / Exam
Quiz
Case Studies / Homework
Assessment Methods and Criteria Others:
Recommended Reading
1. Makridakis, S., Wheelwright, S., Hyndman, R.J. (1998), Forecasting Models and Applications, Wiley
2. Hanke, J.E., Wichern, D. (2008), Business Forecasting, Prentice Hall
Required Reading
Bowerman, B.L., O’Connell, R., Koehler A. (2004), Forecasting, Time Series and Regression, Thomson Brooks
Learning Activities and Teaching Methods Others:
Student Workload:
| Workload |
Hrs |
| Course Readings |
30 |
| Exams/Quizzes |
30 |
Course & Program Learning Outcome Matching:
