GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
FORECASTİNG METHODS/5351303
Course Title: FORECASTİNG METHODS
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
To have knowledge culture analysis of time series and forecasting
To be capable of analyzing and modeling a time series of
Package programs to apply time series topics
Solving a problem or project,is capable of use in preparing the information
Similar problems in other courses disciplines of analysis evaluation of the ability of
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  An overview of forecasting univariate time series . What can be forecast? . Determining what to forecast . Forecasting data and methods . Some cas
2. Week  Forecasting Tools . Graphics . Numerical data summaries . Some simple forecasting methods . Evaluating forecast accuracy
3. Week  Autocorrelation and seasonality
4. Week  White noise and time series decomposition . Time series components . Moving averages . Classical decomposition . X-12-ARIMA decomposition . Seas
5. Week  Exponential smoothing methods . Simple exponential smoothing . Holt's linear trend method . Exponential trend method . Damped trend methods
6. Week  Error-Trend-Seasonal(ETS) models . Holt-Winters seasonal method . A taxonomy of exponential smoothing methods . Innovations state space models for
7. Week  Midterm exam
8. Week  Brown’s general exponential smoothing method
9. Week  Harmonic model ve Fourier analysis of time series dat
10. Week  Transformations and adjustments
11. Week  Stationarity and differencing
12. Week  Autoregressive models
13. Week  Moving average models
14. Week  Estimation and order selection in ARIMA modelling
15. Week  Seasonal ARIMA models
16. Week  Final Exam
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
7
20
 Application
0
0
 Projects
1
30
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
14
4
56
 Searching in Internet and Library
14
2
28
 Material Design and Implementation
7
4
28
 Report Preparing
1
14
14
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
10
10
 Final Exam and Preperation for Final Exam
1
10
10
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3X
4X
5X
6X
7X
8X
9X
10X
 -- NAME OF LECTURER(S)
   (Prof.Dr.Reşat Kasap)
 -- WEB SITE(S) OF LECTURER(S)
   (https://abs.gazi.edu.tr/rkasap)
 -- EMAIL(S) OF LECTURER(S)
   (rkasap@gazi.edu.tr)