COURSE UNIT TITLE

: FORECASTING AND TIME SERIES ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 3915 FORECASTING AND TIME SERIES ANALYSIS ELECTIVE 3 0 0 4

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR SEREN ÖZMEHMET TAŞAN

Offered to

Industrial Engineering

Course Objective

To obtain an understanding and ability to use basic concepts of forecasting and time series, regression methods and moving averages, exponential smoothing methods, adaptive methods and Box-Jenkins model

Learning Outcomes of the Course Unit

1   State, explain and interpret relevant inferential statistics using various data sets for forecasting
2   Explain basics of time series
3   State and explain regression methods and analysis for forecasting
4   State and explain exponential smoothing
5   Explain adaptive method and box-Jenkins model. regression analysis
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 and background information for basic statistics
2 Investigating data structures
3 Moving average and exponential smoothing methods
4 Time series and its components
5 Simple linear regression
6 Multiple regression analysis
7 Regression analysis in time series
8 Mid-term exam
9 Box-Jenkins (ARIMA) method
10 Quantitative forecasting methods, forecasting error analysis
11 Managing forecasting process
12 Project presentation
13 Project presentation
14 Project presentation

Recomended or Required Reading

Textbooks:
1.D. C. Montgomery, C.L. Jennings and M. Kulahci. (2008).Introduction to Time Series Analysis and Forecasting, Wiley-Interscience, USA.

Reference books:
1. F. X. Diebold. (2007). Elements of Forecasting (Fourth Edition), South-Western College Publishing, USA.
2. J. E. Hanke and D. Wichern (2008). Business Forecasting, Prentice Hall, UK.

Planned Learning Activities and Teaching Methods

Instructor notes will be given using blackboard and visual presentations. Additionally, it will be further supported by computer lab work.

Assessment Methods

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


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Tel: 301 76 22
e-mail: seren.ozmehmet@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
Tutorials 1 3 3
Preparations before/after weekly lectures 10 2 20
Preparation for midterm exam 1 15 15
Preparation for final exam 1 15 15
Preparing assignments 4 2 8
Preparing presentations 1 2 2
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 108

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.1553
LO.24
LO.34
LO.4554
LO.555543
LO.65

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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