Content (Syllabus outline)
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| - Decision theory: basics of decision-making, complex decisions' analysis under complete uncertainty and risk, business and economic study cases.
- Multiple criteria decision-making: selected traditional methods based on multi-attribute / utility theory, the Analytic Hierarchy Process, computer supported multiple criteria decision-making, with real-life applications in economics and business.
- Statistics in Management: organizing and visualizing data, descriptive statistics, Basic probability and probability distributions, sampling and sampling distributions, Confidence intervals, Fundamentals of Hypothesis testing – selected tests, simple regresion, Statistical Applications in Quality Management.
- Project optimisation: project definition, project planning and scheduling (project duration and cost with CPM and computer software), project risk estimate (PERT, simulation with computer software), project control, project portfolio.
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Readings
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| Obvezna študijska literature (Compulsory textbooks):
Izbrana poglavja iz:
B. Render, R. Stair, M. Hanna: Quantitative Analysis for Management, Global Edition, 11/E, Pearson Higher Education 2011.
ali: Brandon-Jones, A., Slack, N.: Quantitative Analysis in Operations Management, Financial Times Press, 2008.
Izbrana poglavja iz:
Levine, D.M., Stephan, D.F., Krehbiel, T.C., Berenson, M.L.: Statistics for Managers, 6/E, Pearson Higher Education 2011.
N. Slack, Chambers, S., Harland, C., Harrison, A., and Johnston, R. Operations Management, London: Pitman Publishing, Second Edition, 1998.
J. Heizer, and Render, B. Operations Management. New Jersey: Prentice Hall, 2001.
J. R. Meredith and Shafer, S. M. Operations Management for MBAs. New York: John Wiley & Sons, Inc.1999.
Dodatna študijska literature (Additonal textbooks):
Selected Chapters from:
- V. Belton, T. J. Stewart: Multiple Criteria Decision Analysis - An Integrated Approach. Boston, Dordrecht, London: Kluwer Academic Publishers, 2002.
- C. Zopounidis, P. M. Pardalo, ( |
Objectives and competences
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| Give students the knowledge:
- of formulating business problems that can be solved by statistical techniques and methods
- how to choose and use appropriate statistical tests for hypothesis testing.
- Interpret the results (what the solution means for the problem at hand)
- Obtaining of practical working knowledge by working on business cases and by application of statistical software
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Intended learning outcomes - knowledge and understanding
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| Knowledge and Understanding:
- capacity for analysis and synthesis
- capacity to learn
- identify and use of adequate analytical concepts and instruments
- capacity for analysis of problem and searching for solutions
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Intended learning outcomes - transferable/key skills and other attributes
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| Transferable/Key Skills and other attributes:
- capacity for applying knowledge in practice
- ability to continue studying independently
- capacity for generating new ideas
- capacity to adapt to new situations
- ability to work in an interdisciplinary team
- ability to use the informatics technology
- decision-making
- ethical commitment
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Learning and teaching methods
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| - lectures
- AV presentations
- case studies
- active individual and group work
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