ECTS - Forecasting
Forecasting (IE519) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Forecasting | IE519 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Ph.D. |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| 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;
|
| 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 | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Is independently able to build a problem in the area of study, solve the problem by developing solution techniques and assess the solutions. | X | ||||
| 2 | Is capable of creating a groundwork in the fundamental branches of mathematics as well as in his/her research area | X | ||||
| 3 | follows the latest national and international literature in Mathematics and in his/her area of research; and uses them in his/her related studies | X | ||||
| 4 | observes and adopts the scientific ethical values in his/her professional and social life | X | ||||
| 5 | presents in Turkish and English in academic/scientific events the results of his/her research or the latest studies and findings on a special topic and participates in discussions | X | ||||
| 6 | Develops skills to work independently or as a member of a team | X | ||||
| 7 | Develops competences in the areas of creative and critical thinking, problem solving and producing original studies. Follows recent scientific studies, is capable of making an analysis, synthesis and assessment of the knowledge acquired | X | ||||
| 8 | Is open to lifelong improvement of his/her acquired knowledge, skills and competences. | X | ||||
| 9 | Is able to apply the acquired knowledge and problem-solving skills to interdisciplinary studies, proposes different solution methods to problems in terms of mathematical models and from a mathematical point of view | X | ||||
| 10 | Uses the mathematical based softwares, informatics and communication technologies for scientific purposes | X | ||||
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 | ||