Forecasting (IE519) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Forecasting	IE519	General Elective	3	0	0	3	5

Pre-requisite Course(s)
N/A

Course Language	English
Course Type	Free Elective
Course Level	Social Sciences Master's Degree
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	In this course, the students will be learning the role of forecasting in engineering design.
Course Learning Outcomes	The students who succeeded in this course; Acquaintance of students with the fundamental concepts of forecasting in engineering projects. Ability of students to develop an insight about the role of forecasting for the industrial world. Ability of students to evaluate and solve real life processes and problems using a forecasting model.
Course Content	Forecasting methodology and techniques; dynamic Bayesian modelling; methodological forecasting and analysis; polynomial, seasonal, harmonic and regression systems; superpositioning; variance learning; forecast monitoring and applications; time series analysis and forecasting; moving averages; estimation and forecasting for arma models; arma models;

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Forecasting methodology and techniques
2	Forecasting methods versus Forecasting Systems; Dynamic Bayesian Modelling;
3	Methodological Forecasting and Analysis
4	Polynomial, Seasonal, Harmonic and Regression Systems
5	Superpositioning
6	Variance Learning; Forecast Monitoring and applications;
7	Time Series Analysis and Forecasting; Moving Averages
8	Estimation and Forecasting for ARMA models;
9	ARIMA models
10	Seasonal and Non Seasonal Box-Jenkins Models
11	Midterm
12	Winters’ Exponential Smoothing
13	Decomposition Models
14	Other possible methods
15	Real world applications
16	Final Examination Period

Sources

Course Book	1. Makridakis S.G., Wheelright S.C., Hyndman R.J., Forecasting: Methods and Applications, Wiley, 1997.
Other Sources	2. Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., 4th Edition, June 2006.
	3. Milton, J.S. and Arnold, J.C., Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences, McGraw-Hill, 4th edition, 2002.
	4. Ross, S. Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 3rd edition, 2004.
	5. Triola, M.F., Essentials of Statistics, Addison Wesley,2nd edition, 2004.
	6. Hines, W.W. and Montgomery,D.A., Probability and Statistics in Engineering and Management Science, John Wiley,1990.
	7. Navidi,W. Statistics for Engineers and Scientists, McGraw-Hill, 2008.

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	-	-
Presentation	-	-
Project	1	30
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	1	30
Final Exam/Final Jury	1	40
Toplam	3	100

Percentage of Semester Work	60
Percentage of Final Work	40
Total	100

Course Category

Core Courses
Major Area Courses
Supportive Courses	X
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	1. To be able to combine and use the knowledge of their undergraduate program area with the knowledge of business administration.
2	2. To have knowledge about research methods and techniques and to be able to use them
3	3. To be able to produce creative and constructive solutions in cases of uncertainty and confusion in the field of business
4	Following and evaluating the global and national developments related to businesses and making financial decisions.
5	5. To be able to plan and manage activities for the professional development of employees under his/her responsibility in professional activities and projects in his/her field.
6	6. To be able to produce innovative and creative ideas and to put these ideas into practice
7	7. To be able to carry out a study independently using the knowledge he has in the field of business administration and to take responsibility as a team member in cooperation with other professional groups working in this field.
8	8. To have the ability to reach scientific knowledge in the field of business, to monitor, evaluate and apply the current literature.
9	9. To be able to transfer information about the field of business using effective verbal, written and visual communication methods in the language of learning and professional English.
10	10. To be aware of professional ethics, environmental awareness, sustainability, social responsibility, cultural, social and universal values.
11	11. To be able to work effectively with different disciplines or multicultural teams, to take responsibility, to make risk analysis, to keep up with change, to think critically and to use initiative in problem solving.
12	12. To have the ability to present a research problem, to develop hypotheses, to design research and to reach a conclusion by using qualitative/quantitative methods, by making the necessary literature review, and to have the ability to publish an academic publication as a result.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)	16	3	48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	1	16
Presentation/Seminar Prepration
Project	1	4	4
Report
Homework Assignments	4	4	16
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	1	16	16
Prepration of Final Exams/Final Jury	1	25	25
Total Workload			125