Home  »  Institute of Science »  Master's of Quality Engineering without Thesis

COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
FORECASTING METHODS KAL531 - 3 + 0 10

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITMaster's Degree Without Thesis
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Assistant Professor Mehmet Gülşen
LEARNING OUTCOMES OF THE COURSE UNIT 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
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONThe 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
WEEKTOPICS
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
RECOMENDED 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 METHODSLecture,Questions/Answers,Problem Solving,Other
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term135
Assignment315
Quiz315
Total(%)65
Contribution of In-term Studies to Overall Grade(%)65
Contribution of Final Examination to Overall Grade(%)35
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam122
Preparation for Quiz3412
Individual or group work1414196
Preparation for Final exam12020
Course hours14342
Preparation for Midterm exam12020
Laboratory (including preparation)
Final exam122
Homework3618
Total Workload312
Total Workload / 3010,4
ECTS Credits of the Course10
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
LO1LO2
K1  X  
K2   
K3  X   X
K4    X
K5   
K6    X