At the end of this course, the students; 1) As a tool for decision making under uncertainty is the ability to use appropriate estimation technique to forecast future values 2) Create new knowledge by integrating information from different disciplines 3) Issues that require expertise in the field of scientific research methods to analyze a problem and, as an independent to envision, develop a solution method, resolve, ability to apply the results to evaluate and, if necessary.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction, Definition and Importance of Forecasting, Types of Forecasting Techniques
2nd Week
Definition of Time Series and Movements in Time Series
3rd Week
Analysis of Time Series and its Purpose. Analysis of Movements.
4th Week
Stochastic Processes and Box-Jenkins Stochastic Processes.
5th Week
Definitions and Calculations of Autocovariance, Autocorrelation and Partial Autocorrelation Concepts in Times Series
6th Week
Model Selection for Time Series and Parameter Estimation and its Applications
7th Week
Model Selection for Time Series and Parameter Estimation and its Applications
8th Week
Efficient Parameter Estimation
9th Week
Midterm
10th Week
Forecasting in Stationary and Non-stationary Models
11th Week
Interval Estimation in Box-Jenkins Models
12th Week
General Applications
13th Week
General Applications
14th Week
Discussions on Applications
RECOMENDED OR REQUIRED READING
(1) Box, G.E.P, et al, 1994, Time Series Analysis: Forecasting and Control, Holden Day, S
(2) Bowerman, B.L., O'Connell, R.T., 1979, Time Series and Forecasting, Duxbury.
(3) Vandale, W., 1983, Applied Time Series and Box-Jenksin Models, Academic Pres Inc.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Case Study,Problem Solving,Lecture,Discussion,Questions/Answers
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
30
Project
1
30
Total(%)
60
Contribution of In-term Studies to Overall Grade(%)
60
Contribution of Final Examination to Overall Grade(%)
40
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
Individual or group work
14
14
196
Preparation for Final exam
1
25
25
Course hours
14
3
42
Preparation for Midterm exam
1
25
25
Laboratory (including preparation)
Final exam
1
2
2
Homework
1
14
14
Total Workload
306
Total Workload / 30
10,2
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)