Faculty of Technical Sciences

Subject: Forecasting in Marketing (17.IM1819)

Native organizations units: Department of Industrial Engineering and Engineering Management, Chair of Production Systems, Organization and Management
General information:
 
Category Professional-applicative
Scientific or art field
  • Menadžment i investicije u inženjerstvu
  • Proizvodni i uslužni sistemi, organizacija i menadžment
ECTS 5

The goal of course is to acquire practical knowledge and competencies with respect to business forecasting in the context of marketing and sales, with the special emphasis on time series analysis, that represents an important aspect of managerial decision-making in modern business.

After completion of the course requirements, students will be able to: (1) understand and apply forecasting techniques in business marketing and sales, (2) analyze time series with software packages ("R"), (3) assess business forecasting techniques and choose the most appropriate one, (4) understand seasonal trends in marketing and sales, (5) present and interpret the results of business analysis in written and oral form.

The role and process of forecasting. Time series and their transformations. Data collection and processing. Parametrization. Forecasting techniques. Causal regression. Statistical and economic accuracy and value of forecasting.

Classes include lectures that include practical examples of business forecasting models. Tutorial sessions are held in computer labs.

Authors Title Year Publisher Language
Wilson Keating Business Forecasting, 6 ed. 2009 McGraw-Hill English
James D. Hamilton Time Series Analysis 1994 Princeton University Press English
Hyndman, R. J., Athanasopoulos, G. Forecasting: principles and practice 2014 OTexts English
Course activity Pre-examination Obligations Number of points
Lecture attendance Yes Yes 10.00
Term paper Yes Yes 20.00
Written part of the exam - tasks and theory No Yes 70.00
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Prof. Gradojević Nikola

Full Professor

Lectures
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Prof. Đaković Vladimir

Full Professor

Lectures
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Prof. Đaković Vladimir

Full Professor

Computational classes

Faculty of Technical Sciences

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© 2024. Faculty of Technical Sciences.