COURSE UNIT TITLE

: BUSINESS FORECASTING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
QMT 3001 BUSINESS FORECASTING COMPULSORY 4 0 0 6

Offered By

BUSINESS ADMINISTRATION

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR SABRI ERDEM

Offered to

International Business and Trade
BUSINESS ADMINISTRATION

Course Objective

The course aims to provide students the core issues of generating and implementing business forecasts. Focus is on modern statistical methods that are widely used to generate business forecasts. Specific applications to business include forecasting sales, production, inventory, macroeconomic factors such as interest rates and exchange rates, and other aspects of both short- and long-term business planning.

Learning Outcomes of the Course Unit

1   Have a knowledge understanding of the use of basic tools of forecasting and basic time series analysis techniques.
2   Have a knowledge understanding of the significance of data analysis and model selection criteria.
3   Demonstrate a good understanding of moving average and exponential smoothing forecasting techniques, and the Box-Jenkins method of forecasting.
4   Apply their skills and knowledge to forecast real economic, business and financial time series by moving average and exponential smoothing techniques and the Box-Jenkins method using a statistical package program.
5   Demonstrate their ability to analyze time series in the business environment using the appropriate methods with a high level of confidence.
6   Have experience developing a complete forecast and apply their skills in interpreting computer output and report writing.

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 A review of Basic Statistical Concepts
3 Exploring Data Patterns and an Introduction to Forecasting Techniques
4 Moving Averages and Smoothing Methods
5 Moving Averages and Smoothing Methods
6 Time Series and Their Components
7 Simple Regression
8 Multiple Regression Analysis
9 Multiple Regression Analysis
10 Regression with Time Series Data
11 The Box-Jenkins (ARIMA)-Methodology
12 Judgmental Forecasting and Forecast Adjustments

Recomended or Required Reading

1.Text Book:
Business Forecasting. John E. Hanke and Dean W. Wichern, 9th Edition, Pearson Education, 2009.

2. References
Business Forecasting. J. Holton Wilson and Barry Keating, 6th Edition, Irwin/McGraw-Hill, 2009.
Forecasting Methods and Applications. Spyros Makridais, Steven C. Wheelwright and Rob. J. Hyndman, 3th Edition or later. John Wiley and Sons Inc.

3. Software:
Minitab
SPSS ® (Statistical Package for Social Sciences)
Excel

4. Calculator:
Students will need a scientific calculator for various calculation problems in and out of class, and during exams.

Planned Learning Activities and Teaching Methods

1. Lectures
Class lecture is highly interactive and format is direct. The instructor prompts students for response to questions posed and solicits their thoughts on issues discussed. Lectures will focus on the transfer of basic tools of forecasting and basic time series analysis techniques where comprehension is substantially enhanced by additional elaboration and illustration.
2. Text Readings
Each week, readings from the text will introduce new forecasting concepts and quantitative techniques. Readings provide both the theoretical background and technical skills necessary to generate and interpret business forecasts at an advanced level.
3. Review Sessions and Class Discussions
Review sessions will be handled frequently by the instructor. In-class assignments and homework assignments are the basis of problems to be solved in these sessions. Individual participation by students in classroom discussion is strongly encouraged.
4. Computer Applications
In the laboratory component, a particular statistical package will be introduced to perform analyses of real economic, business and financial time series data.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MT Midterm
2 ASS Assignment
3 FN Final
4 FCG FINAL COURSE GRADE MT * 0.30 + ASS * 0.30 + FN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MT * 0.30 + ASS * 0.30 + RST * 0.40


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

Further Notes About Assessment Methods

None

Assessment Criteria



Language of Instruction

English

Course Policies and Rules

1. It is obligatory to attend at least 70% of the classes.
2. Violations of Plagiarism of any kind will result in disciplinary steps being taken.
3. Students are required to have their own calculator for this course. It will not be allowed to share a calculator during exams. Cellular phones cannot be used as a calculator during an exam.

Contact Details for the Lecturer(s)

Prof. Dr. Sabri Erdem
sabri.erdem@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 4 48
Preparations before/after weekly lectures 10 3 30
Preparing assignments 2 15 30
Preparation for midterm exam 1 15 15
Preparation for quiz etc. 2 10 20
Midterm 1 1,5 2
Quiz etc. 2 1 2
TOTAL WORKLOAD (hours) 147

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.11415424443
LO.2141535443
LO.313153533
LO.413153533
LO.51515344332
LO.6141544545322

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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