Information Package
baskent.edu.tr

Master's of Industrial Engineering with Thesis

END512

FORECASTING TECHNIQUES AND TIME SERIES ANALYSIS

Course Code
END512
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s) -
Learning Outcomes

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. Creat 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 DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionThe role and importance of parameters in decision making process. Dimensions and phases of the forecasting technique. Qualitative and quantitative forecasting methods. Time series and its elements. Indices. Forecasting based on time series.
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 Midterm
9th Week Efficient Parameter Estimation
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
Recommended or Required ReadingBox, G.E.P, et al, 1994, Time Series Analysis: Forecasting and Control, Holden Day, S
Bowerman, B.L., O'Connell, R.T., 1979, Time Series and Forecasting, Duxbury.
Vandale, W., 1983, Applied Time Series and Box-Jenksin Models, Academic Pres Inc.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Practice
  • Presentation
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 Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
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 Work Load306
Total Work Load / 30 (h)10.2
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3
K1 X X
K2 X X X
K3
K4 X X
K5 X X
K6 X X
K7
K8
K9
K10
K11