Course outline


General Information:


School: Economics & Social Sciences

Department: Business Administration

Level of Studies: Undergraduate

Course code: 806

Semester: H

Course title: Business Forecasts


Weekly teaching hours: 4

Type of course: elective

Prerequisite courses: No

Language of instruction and exams: Greek

The course is offered to Erasmus students: No

Course URL: —


Learning outcomes & General Skills:

-     Search, analysis and synthesis of data and information, using the necessary technologies

-     Adaptation to new situations

-     Decision making

-     Autonomous work

-     Teamwork

-     Work in an international environment

-     Work in an interdisciplinary environment

-     Generating new research ideas

-     Project planning and management

-     Respect for diversity and multiculturalism

-     Respect for the natural environment

-     Demonstration of social, professional and ethical responsibility and sensitivity to gender issues

-     Development of criticism and self-criticism

-     Promotion of free, creative and inductive thinking

-     Other skills


Moreover, the course aims to develop the following general skills:

-     Critical ability and self-criticism

-     Ability to cooperate

-     Interpersonal skills

-     Search data using the necessary technologies


Course Content:

-     Introduction to forecasting (categories of forecasting methods, qualitative characteristics of time series, forecasting process)

-     Preparation and analysis of time series (graphical representation of data, statistical analysis of data)

-     Error indices, Decomposition of time series

-     Special events and actions

-     Categories of forecasts (statistical, critical and objective)

-     Prediction horizon, Confidence intervals

-     Forecasting process in business

-     Exponential smoothing method (constant level, linear trend, non-linear trend, and seasonal smoothing models)

-     Regression models (simple and multiple linear regression), Intermittent demand data, Intermittent demand forecasting methods (Croston, SBA and ADIDA methods)

-     Choice of forecasting method

-     Combination of forecasting methods

-     Critical forecasting, Long-term forecasting

-     Scenarios


Teaching & Learning Methods - Evaluation

-     Method of delivery: face-to-face

-     Use of information and communication technologies: Use of information and communication technologies in teaching, laboratory education, communication with students. Electronic communication with students, learning-process support through the “e-class” online platform.



Activities & Semester Workload

Lectures: 13

Laboratory practice: 26

Study of references: 40

Submission of assignments: 40

Exam preparation: 40

Final exams: 2

Total: 161