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
IND 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

ASSOCIATE PROFESSOR SEREN ÖZMEHMET TAŞAN

Offered to

Industrial Engineering

Course Objective

With this course, it is aimed to establish/model the estimation and time series methods that DEU Industrial Engineering Department students may need in their professional lives, to interpret the results obtained as a result of the application with statistical analysis, and also to obtain method application gains by using basic statistical software.

Learning Outcomes of the Course Unit

1   To be able to introduce basic information about forecasting and time series
2   To gain the ability to interpret the results by making the statistical inferences required for estimation on various data
3   To gain the ability to determine the appropriate regression method for the data and to interpret the results
4   To gain the ability to determine the time series method suitable for the data and interpret the results
5   To gain the ability to identify possible models that can be used in the box-jenkins methodology for non-stationary data and to interpret the results
6   To gain the ability to analyze and interpret various estimation problems using basic statistical software.

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
2 Investigating data structures, reviewing basic statistical concepts
3 Introduction to forecasting methods
4 Time series and its components
5 Simple linear regression
6 Multiple regression analysis
7 Multiple regression analysis
8 Analysis in time series
9 Box-Jenkins method and model determination
10 Qualitative forecasting methods, forecasting error analysis
11 Managing forecasting process
12 Case study
13 Case study
14 Case study

Recomended or Required Reading

Textbooks:
1.D. C. Montgomery, C.L. Jennings and M. Kulahci. (2008).Introduction to Time SeriesAnalysis 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


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

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

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

Interview days and times will be notified to the students during the semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
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 3 2 6
Preparing presentations 1 2 2
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 109

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.14
LO.24
LO.345
LO.445
LO.545
LO.644534

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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