Information Package

Master's of Quality Engineering without Thesis

KAL531

FORECASTING METHODS

Course Code
KAL531
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree Without Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. will have an ability to identify, formulate, and forecast parameters of the industrial problems.
  2. will have an ability to apply knowledge of mathematics, science, and engineering to the forecasting problems.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionThe role and importance of forecasting in decision making process. Dimensions and phases of the forecasting technique. Qualitative and quantitative forecasting methods. Time series and its elements. Forecasting based on time series.
Course Contents
WEEK TOPICS
1st Week Role of forecasting in decision making
2nd Week Data collection and analysis
3rd Week Forecasting techniques
4th Week Moving average methods
5th Week Averaging and smoothing methods
6th Week Simple exponential smoothing
7th Week Exponential smoothing with trend
8th Week Midterm
9th Week Exponential smoothing with seasonality
10th Week Simple linear regression model
11th Week Nonlinear regression models
12th Week Multiple linear models
13th Week Time series analysis
14th Week Time series regression models
Recommended or Required Reading(1) Business Forecasting, 7th Ed., Hanke, Wichern, and Reitsch, Prentice Hall, 2001;
(2) Winston W. L. Operations Research, Applications, and Algorithms, 1994, Dixbury Press
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Other
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 35
Assignment 3 15
Quiz 3 15
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 3 4 12
Individual or group work 14 14 196
Preparation for Final exam 1 20 20
Course hours 14 3 42
Preparation for Midterm exam 1 20 20
Laboratory (including preparation)
Final exam 1 2 2
Homework 3 6 18
Total Work Load312
Total Work Load / 30 (h)10.4
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2
K1 X
K2
K3 X X
K4 X
K5
K6 X