Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

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

Offered By

BUSINESS ADMINISTRATION

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR AYSUN KAPUÇUGIL IKIZ

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

ECN 1904 - PRINCIPLES OF MACROECONOMICS

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Introduction to Forecasting
2	A review of Basic Statistical Concepts	Introducing the Forecasting Project Areas and Project Details
3	Exploring Data Patterns and an Introduction to Forecasting Techniques	Autocorrelation Analysis, Choosing a Forecasting Technique, Measuring Forecasting Error, Determining the Adequacy of a Forecasting Technique.
4	Moving Averages and Smoothing Methods	Forecasting Methods Based on Averaging, Exponential Smoothing, Holt Winters Methods, Trend and Seasonal Components In-class activity: Computer Applications -Lab Exercises Submission of Project Proposal to the Instructor
5	Time Series and Their Components	Decomposition, Seasonal Adjustments
6	Simple Regression	Forecasting with Simple Regression Line, Decomposition of Variance, Hypothesis Testing, Analysis of Residuals, Variable Transformations In-class activity: Computer Applications -Lab Exercises
7	Multiple Regression Analysis	Correlation Matrix, Multiple Regression Model and Interpreting the Coefficients, Inference for Multiple Regression Models, Dummy Variables, Multicollinearity, Selecting the Best Equation, Regression Diagnostics.
8	Regression with Time Series Data	Autocorrelation, Durbin Watson Tests, Solutions to Autocorrelation Problems, Heteroscedasticity Problem, Econometric Forecasting, Cointegrated Time Series. In-class activity: Computer Applications -Lab Exercises
9	The Box-Jenkins (ARIMA)-Methodology	Box-Jenkins Methodology, Implementing the Model-Building Strategy, Introducing p, d, q terms, Optimizing ARIMA models. In-class activity: Computer Applications -Lab Exercises
10	Judgmental Forecasting and Forecast Adjustments	The Delphi Method, Scenario Writing, Combining Forecasts
11	Forecast Project Presentations	Submission of Forecast Project to the instructor via email and printout (Due at the beginning of the week)
12	Forecast Project Presentations

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)

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	TP	TermProject
3	PRS	Presentation
4	FCG	FINAL COURSE GRADE	MT * 0.40 + TP * 0.40 + PRS * 0.20

Further Notes About Assessment Methods

1. Exam
Exam will measure the concepts introduced in the text readings and provide an opportunity to apply the techniques learned to solve practical forecasting problems.

2. Term Project and Presentation
In this course, Term Project refers to Forecast Project. Students are required to complete a Forecast Project which allows them to apply the concepts and forecasting skills they have developed to a topic of personal or professional interest, like analysis of time series of an exchange rate, the price of a stock or a stock index, etc.

Each week as making progress through the text and new forecasting techniques are introduced, the students will apply these new skills to their project. By the end of the term, students will have developed a rather sophisticated forecast.

By completing the project, students will improve analytical and communication skills through identifying and applying forecasting techniques to the real economic, business and financial problems. Project reports and presentations will enable students improve their competency using the language of modern statistics to communicate the results.

Homework problems will be also assigned frequently in line with the project. It is imperative that a student works and understands these problems to successfully complete the project. It is strongly recommended the students to work all homework problems as a study tool for the exam as well as the project.

By completing homework assignments, each student will enhance analytical skills, as well as, improve competency utilizing Spreadsheet Software and a statistical package for data entry and analysis. By actively participating in class discussions and in-class assignments, each student will improve communication and analytical skills through learning forecasting tools and business applications.

Assessment Criteria

1. In exam, there will be one major part for each chapter. In each part, one or more questions are asked. Depending upon the general performance level of the students and the instructor's own initiative, the bell-curve calculations might be used to transform the grades. If any exam question is left unanswered, the value of that question will be subtracted from the exam score. If only the answer is given (i.e., no work showing how that answer was determined), the question will be graded at 25% of its value.

2. A good attendance record will bring the grade up one level, for grades on the boundary between two grade levels.

3. The forecasting project will be graded by the instructor. Project will be evaluated for such factors as apparent understanding of the topic, originality of treatment and discussion, accuracy of results, comprehensiveness of the report's content and depth of the analysis, clarity and mechanics of presentation such as organization, format, punctuation, grammar, and quality of exhibits and charts.

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. Delayed forecast project reports will suffer grade decay equivalent to one letter grade per day late.
4. 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)

Assist.Prof. Aysun Kapucugil Ikiz
Email: aysun.kapucugil@deu.edu.tr Room #: 126/A Office Phone: 232.3018286

Teaching Assistant: Mehmet Çağlıyangil
Email: mehmet.cagliyangil@deu.edu.tr Room #:123

Office Hours

To be announced.

Work Placement(s)