COURSE UNIT TITLE

: FORECASTING AND TIME SERIES ANALYSIS FOR MANAGEMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5012 FORECASTING AND TIME SERIES ANALYSIS FOR MANAGEMENT ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR SEREN ÖZMEHMET TAŞAN

Offered to

INDUSTRIAL ENGINEERING (ENGLISH)
Industrial Engineering - Thesis (English) (Evening Program)
INDUSTRIAL ENGINEERING (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM) (ENGLISH)

Course Objective

The main objective of this course is to develop the skills needed to do empirical research in fields operating with time series analysis techniques, considering both theoretical and practical aspects. The course aims at deeper understanding of the techniques, description of the generating mechanism, the forecasting of future values, and optimal control of a system exclusively with discrete time series observed at equal intervals. The course will also emphasize recent developments in time series analysis and will present some open questions and areas of ongoing research.

Learning Outcomes of the Course Unit

1   State, explain and interpret relevant inferential statistics using various data sets for forecasting
2   Compute and interpret a correlogram and a sample spectrum
3   State and explain regression methods and analysis for forecasting
4   State and explain smoothing
5   Compute forecasts for a variety of linear methods and models
6   Explain the usage of software for forecasting

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to forecasting systems
2 Regression methods and moving averages
3 Exponential Smoothing Methods
4 Discounted Least squares and direct smoothing
5 Smoothing models for seasonal data
6 Forecasting
7 Midterm Exam
8 Analysis of forecast errors
9 Adaptive-Control forecasting methods
10 The Box-Jenkins models
11 The Box-Jenkins models
12 The Box-Jenkins models
13 The Box-Jenkins models
14 Future research

Recomended or Required Reading

Textbooks:
D. C. Montgomery, C.L. Jennings and M. Kulahci. (2008).Introduction to Time Series Analysis and Forecasting, Wiley-Interscience, USA.
Hamilton, James D. Time Series Analysis. Princeton, NJ: Princeton University Press, 1994.

Reference books:
F. X. Diebold. (2007). Elements of Forecasting (Fourth Edition), South-Western College Publishing, USA.
J. E. Hanke and D. Wichern (2008). Business Forecasting, Prentice Hall, UK.
William. S. Wei, Time series Analysis; Univariate and Multivariate Methods, 1990, Addison Wesley, USA.
S. Makridakis, Steven C. Wheelwright, Forecasting Methods for Management, 1989, John Wiley and Sons, USA.
Wayne Fuller, Introduction to Statistical Time Series, 1996, Wiley, USA.
George E. P. Box and Gwilym M. Jenkins, Time Series Analysis: Forecasting and Control, 1976, Holden Day, USA.

Planned Learning Activities and Teaching Methods

Instructor notes will be given using blackboard and visual presentations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.35 + PRJ * 0.15 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.35 + PRJ * 0.15 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term exam: 20%, Homework : 40%, Final exam: 40%

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Tel: 301 76 19, e-mail: serdar.tasan@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 6 78
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparing assignments 1 35 35
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 196

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.11523415
LO.2125551
LO.32315221
LO.41211
LO.534212
LO.612551

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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