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FACULTY of ENGINEERING / DEPARTMENT of CIVIL ENGINEERING

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FACULTY of ENGINEERING / DEPARTMENT of CIVIL ENGINEERING /
Katalog Ana Sayfa
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END3020Forecast Techniques3+0+0ECTS:5
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Elective
DepartmentDEPARTMENT of INDUSTRIAL ENGINEERING
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face
Contact Hours14 weeks - 3 hours of lectures per week
LecturerDoç. Dr. Hüseyin Avni ES
Co-Lecturer
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
To be informed about the forecast, which is a sub-element of the decision-making about the future, to ensure the application of the correct forecasting technique for the situation encountered,To be able to use the necessary statistics and computer aided programs and to interpret the results correctly.
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : Determine the appropriate forecast method according to the problem. Selects the appropriate model for the specified forecast methods21,3
LO - 2 : Measures and evaluates the error for estimates, Forecast the future111,3
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome

 
Contents of the Course
Presentation of forecasting techniques and operation of forecasting system, Evaluation of qualitative and quantitative forecasting methods, Performing computer-aided applications of statistical and artificial intelligence-based forecasting techniques and interpretation of results, Presentation of a real forecasting application
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Forecast-Plan Concepts,Forecasting Areas, Forecast Types
 Week 2Characteristics of Forecasting, Qualitative and Quantitative Forecasting Techniques, Operation of Forecasting System
 Week 3Recalling Basic Statistical Concepts (Correlation, Standard Deviation, Hypothesis Testing, Student-t and Normal Distribution etc.)
 Week 4Investigation of Data Structure
 Week 5Selection of Appropriate Forecasting Techniques,, Experimental Evaluation of Forecasting Techniques, Measurement of Forecast Error
 Week 6Naive Models, Meaning Estimation Methods (Simple Averages, Moving Averages, Weighted Moving Averages, Double Moving Averages)
 Week 7Exponential Correction Methods (Holt and Winter)
 Week 8Minitab/SPSS Application
 Week 9Midterm Exam
 Week 10Simple Linear Regression, Variance Decomposition, Factor of Analysis, Residual Analysis, Variable Transformations
 Week 11Multiple Regression Analysis, Regression Significance, Dummy Variables, Multicollinearity, Selecting the Regression Equation
 Week 12Introduction to ARIMA methodology for stationary series
 Week 13Minitab/SPSS Application
 Week 14Forecasting with artificial intelligence methods
 Week 15Project and Homework Presentations
 Week 16Final exam
 
Textbook / Material
1Çekerol, G.S., Ulukan, A. (2012). Kantitatif Tahmin Yöntemleri, Nisan Kitabevi.
2Hanke, J.E. and D.W. Wichern (2008). Business Forecasting. 8thEdition, Pearson Education International; Harlow, Essex.
 
Recommended Reading
1Makridakis, S, S.C. Wheelwright, and R.J. Hyndman (1988). Forecasting: Methods and Applications, Third Edition. John Wiley and Sons; New York.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 11/04/2019 1,5 30
Project 14 27/05/2019 6 20
End-of-term exam 16 27/05/2019 1,5 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 14 42
Sınıf dışı çalışma 3 14 42
Arasınav için hazırlık 2.5 8 20
Arasınav 2 1 2
Proje 3 10 30
Dönem sonu sınavı için hazırlık 2 6 12
Dönem sonu sınavı 2 1 2
Total work load150