Information Package

Program of Industrial Engineering (English 30%)

END352

FORECASTING TECHNIQUES

Course Code
END352
Semester
-
Theory+Practice
3 + 0
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Develop fundamental data analysis skills within the context of forecasting model development.
  2. Identify and classify methods and models used in business forecasting
  3. Have exposure to computer programs used for forecasting.
  4. Gain an ability to discuss results and propose recommendations based on forecasting results.
  5. Formally present business forecast solutions
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionImportance of forecasting in decision making process. Quantitative and qualitative forecasting techniques. Time series analysis, moving averages and exponential smoothing. Other forecasting techniques.
Course Contents
WEEK TOPICS
1st Week Role of forecasting in decision making. What is forecasting?
2nd Week Review of statistical concepts
3rd Week Data collection and analysis. Data Patterns
4th Week Forecast evaluation techniques
5th Week Moving Averages
6th Week Exponential Smoothing
7th Week Exponential smoothing with trend and seasonality
8th Week Simple linear regression model
9th Week Midterm
10th Week Multi-variable regression models
11th Week Time series analysis
12th Week Box-Jenkins ARIMA models
13th Week ARIMA Model Verifications
14th Week Combining Forecasts
Recommended or Required ReadingBusiness Forecasting (9th Edition), John E. Hanke, Dean Wichern, Prentice Hall; 9 edition (2009)

Forecasting: Methods and Applications, Spyros Makridakis, Steven C. Wheelwright, Rob J. Hyndman, Wiley; 3 edition (December 1997)
Planned Learning Activities and Teaching Methods
  • Lecture
  • Case Study
  • Presentation
  • Problem Solving
  • Discussion
  • Project
  • Questions/Answers
  • Report Preparation
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 25
Quiz 1 15
Project 1 20
Attendance 1 5
Total(%) 65
Contribution of In-term Studies to Overall Grade(%) 65
Contribution of Final Examination to Overall Grade(%) 35
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz 1 4 4
Individual or group work 14 2 28
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 8 8
Total Work Load136
Total Work Load / 30 (h)4.53
ECTS Credit of the Course5
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3 LO4 LO5
K1 X X
K2 X X
K3 X X
K4 X X
K5 X
K6 X
K7 X X
K8 X
K9 X X
K10 X
K11